Systems and methods for assessing electrical connectivity between elements of assay devices

ABSTRACT

Disclosed are devices, systems and methods for assessing the integrity of electrical connections between elements of interfacing electronic devices. In some aspects, a system includes an analysis device having electronics that interface with an assay cartridge inserted into the analysis device, wherein the analysis device is configured to conduct a preflight test in which impedance values for each circuit between the assay cartridge and analysis device are rearranged and assessed to determine the electrical connection integrity of the assay cartridge to the analysis device prior to implementing the assay.

TECHNICAL FIELD

This patent document relates to medical devices and, more particularly,to medical devices for the detection and/or analysis of target analytesfrom patient samples.

BACKGROUND

Preventable medical errors are now the third leading cause of death inthe United States at more than 250,000 per year. For example,preventable medical errors can arise when automated detection systemsfor nucleic acid or other biomolecular testing do not performaccurately. But, placing strict controls on detection systems mayprevent valid sample from being processed resulting in waste and timedelay. This can lead to serious problems for a patient whose sample mustbe analyzed rapidly. For example, critical time could be lost to obtainnew samples from the patient and re-run a test. In some cases, such adelay can be deadly, such as for detection systems which detectorganisms that cause sepsis. Recent studies have shown that patientswith severe sepsis or septic shock showed an increased likelihood ofdeath of 7.6% for every hour in which antibiotic therapy is not applied,such as shown in Liang et al., Empiric Antimicrobial Therapy in SevereSepsis and Septic Shock: Optimizing Pathogen Clearance, Curr Infect DisRep. 2015 July; 17(7): 493. Survival rates could increase if detectionsystems performed accurately.

SUMMARY

Disclosed are devices, systems and methods for assessing the integrityof electrical connections between elements of interfacing electronicdevices, such as between circuits of different components, modules,units or apparatuses of an assay device for detecting a target analyte,which can include electrical connections between an assay cartridge andan instrument bay of the assay device. Assessing the integrity ofelectrical connections between interfacing electronic devices couldincrease validity rates of assay devices for detecting target analytes,which may help to reduce preventable medical error and save lives.

In some implementations, an assay test cartridge is initially insertedinto analysis device and pre-examined before implementing an assay.Impedance values for one or more electrodes on the assay test cartridgeare measured to generate a working impedance value (WIV) for each of theone or more electrodes. The working impedance values are then ordered tomatch at least one impedance reference order (RO). The RO can bedetermined based on a statistically representative distribution of theimpedance values derived from devices of the same type as the workingdevice. A quality of the fit (QOF) is then determined and used forvalidating the integrity of the assay cartridge. For example, if thequality of the fit (QOF) is above a predetermined threshold, a passsignal is generated, and the cartridge is processed by the medicaldevice instrument; whereas, if a cartridge fails such preflightimpedance testing, it is ejected and can be re-tested in the same bay orin a different bay.

In some example embodiments in accordance with the disclosed technology,a method for assessing electrical connection integrity of an assaycartridge interfaced with an assay processing device includesestablishing an electrical connection between the assay cartridge andthe assay processing device; measuring electrical signals to determineimpedance values associated with at least two circuits between the assaycartridge and the assay processing device; organizing the impedancevalues to form a new data stream; analyzing the new data stream todetermine a quality factor; and sending a command signal for initiatingan assay procedure when the quality factor is at or above apredetermined standard.

In some example embodiments in accordance with the disclosed technology,a method for assessing electrical connection integrity of a first deviceand second device includes establishing an electrical connection betweenthe first device and second device; measuring electrical signals todetermine a first data block associated with at least three electrodeson the first device; organizing the first data block to form a seconddata block; analyzing the second data block according to a first factor;and sending a signal for initiating a procedure when the first factor isat or above a predetermined standard.

In some example embodiments in accordance with the disclosed technology,an assay processing device for assaying a patient sample, including anelectronic unit that interfaces with a printed circuit board (PCB) on anassay cartridge, an impedance module, a pattern module, and a qualifiermodule.

In some example embodiments in accordance with the disclosed technology,an assay processing device including (i) an electronic unit thatinterfaces with an assay cartridge when inserted in the assay processingdevice, wherein the electronic unit includes a plurality of electricalconductor sites to contact at least some of a plurality of electricalinterface connections of the assay cartridge, and (ii) a data processingunit to control functionality of the assay processing device and/orprocess acquired data to produce an output for the assay processingdevice, wherein the assay processing device is configured to conduct apreflight test assessing electrical connection integrity of the assaycartridge with the electronic unit, wherein, in conducting the preflighttest, the assay processing device measures an electrical signal todetermine an impedance value associated with at least some of theelectrodes of the assay cartridge; analyzes the determined impedancevalue to evaluate a quality factor (also referred to as a QOF factor) ofthe electrical connection between the assay cartridge and the electronicunit of the assay processing device; and determines a command forinitiating an assay procedure when the quality factor is at or above apredetermined standard, or determines a command for ejecting the assaycartridge from the assay processing device when the quality factor isbelow the predetermined standard.

In some example embodiments in accordance with the disclosed technology,a method for preflight test assessing electrical connection integrity ofan assay cartridge interfaced with an assay processing device includesestablishing an electrical connection between (i) an assay cartridgeincluding a printed circuit board (PCB) having a plurality of electricalinterface connections corresponding to a plurality of electrodes in thePCB and (ii) an electronic unit of an assay processing device, whereinthe electronic unit includes a plurality of electrical conductor sitesto contact at least some of the plurality of electrical interfaceconnections of the assay cartridge PCB; measuring an electrical signalto determine an impedance value associated with at least some of theelectrodes of the assay cartridge PCB; analyzing the determinedimpedance value to evaluate a quality factor of the electricalconnection between the assay cartridge PCB and the electronic unit ofthe assay processing device; and determining a command for initiating anassay procedure when the quality factor is at or above a predeterminedstandard, or determining a command for ejecting the assay cartridge fromthe assay processing device when the quality factor is below thepredetermined standard.

The subject matter described in this patent document can be implementedin specific ways that provide one or more of the following features.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a data plot depicting the average impedance for electrodeson PCBs of assay cartridges run in TTM-2 bays and plotted monotonically.

FIG. 2A shows a data plot depicting average impedance values forelectrodes on PCBs of assay cartridges run in TTM-2 bays and plottedmonotonically that fit a linear line.

FIGS. 2B-2D show data plots depicting impedance data from threedifferent cartridges run in example TTM-2 bays.

FIG. 3 shows a data plot depicting the worst standard error of the fit(RFT) from each run in the TTM-2 bay.

FIG. 4 shows a data plot depicting the data re-ranked according to amaximum scaled error across the electrodes for each run in the TTM-2bay.

FIG. 5 shows a data plot depicting the data re-ranked according to aminimum scaled error across the electrodes for each run in the TTM-2bay.

FIG. 6A shows a data plot depicting the average impedance for electrodeson PCBs of assay cartridges when run in an TTM-3 bay and plottedmonotonically.

FIG. 6B shows a data plot depicting average impedance values forelectrodes on PCBs of assay cartridges run in TTM-3 bays and plottedmonotonically that fit a linear line.

FIG. 6C shows a data plot depicting a data set from a single cartridgewith a defect at electrode 125.

FIG. 7 shows a data plot depicting the standard error of the fit (RFT)for each run on a TTM-3 bay.

FIG. 8 shows a data plot depicting the data re-ranked according to themaximum scaled error across the electrodes for each run on a TTM-3 bay.

FIG. 9 shows a data plot depicting the data re-ranked according to theminimum scaled error across the electrodes for each run on a TTM-3 bay.

FIG. 10 shows a data plot depicting the average impedance for electrodesPCBs of assay cartridges run in TTM3-b bays and plotted monotonically.

FIG. 11 shows a data plot depicting the standard error of the fit (RFT)for each run in a TTM3-b bay.

FIG. 12 shows a data plot depicting the data re-ranked according to themaximum scaled error across the electrodes for each run in a TTM3-b bay.

FIG. 13 shows a data plot depicting the data re-ranked according to theminimum scaled error across the electrodes for each run in a TTM3-b bay.

FIG. 14A shows a data plot depicting the average impedance forelectrodes on PCBs of assay cartridges run in Lenthor bays and plottedmonotonically.

FIG. 14B shows a data plot depicting impedance data from a passingcartridge on a Lenthor type bay, plotted with the linear fit to thedata.

FIG. 15 shows a data plot depicting the standard error of the fit (RFT)for each run in a Lenthor bay.

FIG. 16 shows a data plot depicting the data re-ranked according to themaximum scaled error across the electrodes for each run in a Lenthorbay.

FIG. 17 shows a data plot depicting the data re-ranked according to theminimum scaled error across the electrodes for each run in a Lenthorbay.

FIGS. 18A and 18B show diagrams of example embodiments of a system forassessing electrical integrity between interfacing devices, such as aPCB of an assay cartridge electronically connected to an analyticalinstrument.

FIG. 18C shows a diagram of an example embodiment of the data processingmodule shown in FIGS. 18A and 18B.

FIG. 18D shows a diagram of an example method for assessing electricalconnection integrity of interfacing electronic devices in accordancewith the disclosed technology.

FIG. 18E shows a diagram of an example method for analyzing impedancevalues to evaluate a quality factor of electrical connection betweeninterfacing electronic devices in accordance with the disclosedtechnology.

FIGS. 19-22 show diagrams of example embodiments of a method forassessing electrical connections based on rearrangement of an input datastream in an analysis system, such as an assay cartridge qualificationsystem.

FIG. 23 shows a diagram of an example printed circuit board for an assaycartridge device.

FIG. 24 shows a data plot depicting example average impedance values foreach electrode across multiple bays of different types of assaycartridge bays.

FIG. 25 shows a data plot depicting average impedance values associatedwith an example TTM3 bay, which illustrates the difficulty in making anaccurate pass/fail call on a cartridge with a defect.

FIGS. 26A and 26B show schematic illustrations of an example connectorboard and plate of an example embodiment of a connector board assemblyof an assay cartridge bay.

FIG. 27 shows a diagram of an example data block sequence of n datablocks formed into an array in accordance with the disclosed technology.

FIG. 28 shows a diagram of an example an affinity matrix formed inaccordance with the disclosed technology.

FIG. 29 shows a diagram of an example an affinity matrix derived fromthe affinity matrix shown in FIG. 28.

FIG. 30 shows a diagram of an example an affinity relationship matrixderived from the affinity matrix shown in FIG. 29.

FIG. 31A shows a schematic illustration of an example embodiment of ananalysis device of an assay system in accordance with the presenttechnology.

FIGS. 31B-31D show schematic illustrations depicting portions of anexample electronic device for an assay cartridge processing bay and ofan example PCB in electrical connection.

FIG. 31E shows a schematic illustration depicting portions of an assaycartridge processing bay (bottom bay).

FIG. 32 shows a data plot depicting example impedance measurements at 10kHz and 100 kHz.

DETAILED DESCRIPTION

During the past decade or so, there has been great interest indeveloping microfluidic based devices, often referred to asLab-on-a-Chip (LoC) or Micro Total Analysis Systems (μTAS), with goalsof minimal reagent usage, shorter measurement turnaround time, lowerexperiment cost, and higher data quality, etc. Microfluidics devicetechnology finds applications in printing, fuel cell, digital display,and life sciences, etc.

Microfluidics technology can be broadly categorized into channel-basedcontinuous-flow systems, including droplets-in-microfluidic-channelsystems or droplet actuators on electrowetting systems. Dropletactuators are used to conduct a wide variety of droplet operations. Forexample, a droplet actuator typically includes two plates separated by agap. The plates include electrodes for conducting droplet operations.The space can be filled with a filler fluid that is immiscible with thefluid that is to be manipulated on the droplet actuator. The formationand movement of droplets are controlled by electrodes for conducting avariety of droplet operations, such as for droplet transport and dropletdispensing. One or both of the plates of the droplet actuator may bemanufactured using a printed circuit board (PCB). The functionality ofthe droplet actuator is dependent on, for example, the electricalconnection made between the PCB and the working device.

An assay is an analysis performed to determine the presence or amount ofa substance of interest. Some assay techniques utilize microfluidics fortransporting, mixing, and/or processing various fluids in the assay,including samples containing the target substance of interest. Amicrofluidic device is an instrument that can control the behavior ofvery small amounts of fluid (e.g., such as μL, nL, pL, and fL) throughchannels with dimensions in relatively small dimensions, e.g., thesub-millimeter range. Microfluidic devices can be implemented to obtaina variety of analytical measurements including molecular diffusionvalues, chemical binding coefficients, pH values, fluid viscosity,molecular reaction kinetics, etc. Microfluidic devices can be built onmicrochips to detect, separate and analyze biological samples, which canalso be referred to as a lab-on-a-chip. For example, a microfluidicdevice may use biological fluids or solutions containing cells or cellparts to diagnose diseases.

Some assay devices, such as some automated electrochemical detectionsystems for nucleic acid or other biomolecular testing, include (a) aninstrument bank that includes one or more cartridge bays havingelectronics that interface with an assay cartridge (also referred to asa biochip cartridge) inserted in the bay for analyzing a sample providedin the biochip cartridge, and (b) a base station that includes aprocessing unit to control functionality of the assay device and/orprocess the acquired data to produce an output for the electrochemicaldetection-based assay. The base station can include a user interface(e.g., display). In some implementations, the instrument bank and thebase station are embodied in a single housing, whereas in otherimplementations the instrument bank and base station are embodied asseparate or separable devices.

In some examples, a cartridge bay can include (i) an upper regioncomprising actuators for manipulating a liquid reagent module (LRM); and(ii) a lower region comprising a printed circuit board (PCB) havingelectrical connections for connecting to the biochip cartridge. Someexamples of an analysis cartridge bays and base stations are describedin U.S. Pat. Nos. 9,598,722 and 9,957,553, which are herein incorporatedby reference in their entirety for all purposes.

In some examples, an assay (biochip) cartridge can include (i) an upperregion comprising a liquid reagent module (LRM); and (ii) a lower regioncomprising a printed circuit board (PCB) having electrical connectionsfor connecting to a bay and electrowetting grid and detectionelectrodes. Some examples of an analysis cartridge are described in U.S.Pat. Nos. 9,598,722 and 9,957,553, which are herein incorporated byreference in their entirety for all purposes.

If the electrical connections between the analysis device and cartridgedo not properly connect to provide the proper signal paths in theelectrowetting grid and detection electrodes on the cartridge PCB, theassay device cannot properly process the biochip cartridge and aninvalid test result may be reported. Some examples of such automatedelectrochemical detection systems are described in U.S. Pat. Nos.9,598,722 and 9,957,553, which are herein incorporated by reference intheir entirety for all purposes.

Some examples of implementing an assay (also referred to as “processingthe cartridge” or “launching the assay” or “running an assay” or“perform an assay”) include one or more of the following assayprocessing steps: cell lysis, amplification, and detection. In variousembodiments, detection is dependent on detection of color,radioactivity, fluorescence, chemiluminescence or electrochemicalsignals, such as in an automated electrochemical detection system. Whilethe systems and methods are not limited to a specific cartridges/assays,exemplary processing steps are described in U.S. Pat. Nos. 9,598,722 and9,957,553, which are herein incorporated by reference in their entirety.

In some implementations, when a biochip cartridge is loaded into theinstrument bay of an analysis device, it makes contact with the bay viapogo pins. In this way, the bay can transmit data, control signals, andpower to the cartridge PCB, and the cartridge PCB can transmit data tothe bay. The pogo pins make electrical contact with the cartridge PCB.An example of such electrical connections using pogo pins is shown inFIG. 43 of U.S. Pat. No. 9,498,778 and FIG. 29 of U.S. Pat. No.9,957,553, which are herein incorporated by reference in their entiretyfor all purposes. In some implementations, the electronics of the bayportion of the instrument bay includes a PCB that serves as a mountingsurface for the circuit assembly on the insertable biochip cartridge.

Typically, when PCBs are manufactured, the electrodes are tested.Generally, the integrity of the of the printed circuit board is assessedbased on whether the electrical connector, such as a pin or solder pad,is properly connected to an electrical signal path on the circuitassembly. For example, a PCB is tested to evaluate if the electricalconnector is properly soldered to the signal path or wire trace. Animproperly soldered electrical connector may result in an open circuitor a short circuit on the PCB. But, this type of testing does notmeasure whether there is a proper “fit” between the electronics of acartridge for an analysis device and the electronics of the analysisdevice. Moreover, this type of testing also does not account forbay-to-bay variability in baseline or actual assay measurements acquiredat the instrument bank of an assay device. These improper “fit” issuesand bay-to-bay variability problems result in an “invalid” output, orworse, result in testing errors such that an infecting pathogen maypossibly go undetected, e.g., leading to false negative results.

Thus, after a cartridge is loaded into an analysis device, the analysisdevice should perform a preflight test to confirm that the analysisdevice and cartridge are properly connected before launching the assay.A pre-flight test evaluates whether the assay cartridge is properlyconnected to the automated electrochemical detection system. Forexample, if even one electrode on the assay cartridge is not properlyconnected to the automated electrochemical detection system, thedetection system's ability to process the sample and accurately detectan infection is hampered. Accurately catching runs with poor connectionsin a preflight connection analysis allows a retry of the cartridgebefore the sample is consumed by processing the assay, potentiallyincreasing validity rates and preserving samples. For example, failureto conduct a preflight test to confirm that the electrical connectionsbetween the bay and cartridge (e.g., at the PCB) are properly connectedcould result in an assay being performed, but knowingly or unknowinglyfail, e.g., because one or more electrical connections between the bayand cartridge are improper. Failure of the assay may occur in manyforms. For example, the sample may not move properly in the microfluidicchannels or nodes in the cartridge, may improperly mix, may sufferimproper amplification and/or detection, and thereby produce a failedtest result or an incorrect result (e.g., false negative).

In some implementations, a preflight test includes measurements of theimpedances of the bay's electrical connections to the cartridge. Onemethod to evaluate the connection between an assay cartridge and ananalysis device is to run an impedance test and compare the impedancemeasurement to a predetermined threshold (referred to as the impedancethreshold method). However, Applicants have discovered that thevariation of trace impedance between two analysis devices can besignificant because of bay-to-bay variability, cartridge-to-cartridgevariability, along with measurement variability. This variability canlead to assay cartridges with poor connections being processed leadingto incorrect results (e.g., false negatives or invalids).

In some examples, the pre-flight impedance measurements are scattereddata, e.g., the impedance value from electrode 1 bears no relation tothe impedance value from electrode 2. As such, the impedancemeasurements must be compared against expected ranges for each electrode(e.g., electrode 1 compared to expected data for electrode 1, andelectrode 2 compared to expected data for electrode 2). For example, animpedance measurement reported at a higher value than expected may occurdue to a poor connection to an electrode resulting from an “open”circuit connection, and an impedance measurement reported at a lowervalue than expected may occur due to a poor connection to an electroderesulting from an “short” circuit connection. If any measurementindicates a poor connection, the bay should not start the assay in thatbay. This ensures that sample is not wasted on a run which cannotproduce a valid result. For example, the problem may be due to a usererror in inserting the cartridge into the bay; the cartridge may bepre-flight tested again upon a repeated insertion into the bay. Or forexample, since the problem may be due to the electronics of that bay,the cartridge which was not processed can be loaded and retested inanother bay of the instrument bank.

When a PCB is loaded into a testing device, it cannot be assumed that itis loaded and connected properly each time. For example, impedancemeasurements during pre-flight analysis of the cartridges havesignificant target impedance variability. In this context, the term“target” is used because, in reality, some amount of variation aroundthe nominal impedance occurs due to process variations in themanufacture of the bay and the PCBs and loading techniques. Currently,such impedance variations may be controlled to within +/−10% of thetarget impedance. Applicants discovered that the target/impedance limitchanged over the course of the year. In some cases, for example, theupper and lower limit widened and in other cases they narrowed (data notshown).

However, relying on “target” impedance measurements has proven to beprone with false failures and false passes because of bay-to-bayvariability, cartridge-to-cartridge variability, along with measurementvariability. For example, a good connection between one cartridge/baypair may produce an impedance measurement that is equal to an impedancemeasurement from another cartridge/bay pair with a poor connection.Thus, the connection between a cartridge/bay may be characterized asgood or poor if a different bay, a different cartridge, or a differentcartridge and different bay are used. This inaccuracy has allowed runswith poor connections to be processed and has prevented runs with goodconnections from being processed, e.g., resulting in waste, time delay,and increased risk to the patient. Accurately catching runs with poorconnections in a preflight connection analysis allows a retry of thecartridge before the sample is consumed by processing the sample,potentially increasing validity rates and preserving samples.

Disclosed are devices, systems and methods for assessing the integrityof electrical connections between elements of interfacing electronicdevices. The disclosed methods can be implemented by a variety ofelectronic systems that electrically interface different circuits,electronic components, modules, units or apparatuses. Whileimplementations of the disclosed technology are suitable for a varietyof applications, the following disclosure describes several embodimentsof the disclosed methods, systems and devices for assay systems capableof detecting a target analyte, which include assessing the electricalconnections between an assay cartridge and an instrument bay of theassay device.

Example embodiments and implementations of the devices, systems andmethods are described for an automated electrochemical detection assaydevice to characterize the impedance of electrical connectionscorresponding to an electrode of an assay sample cartridge and anelectrode of an assay processing bay of an analysis device. In someimplementations, the characterized impedance of the electricalconnections between the electrodes of the analysis device and cartridgeis used to determine whether to conduct the assay using the samplecartridge in the processing bay. In some implementations, thecharacterized impedance of the electrical connections between theelectrodes of the analysis device and cartridge is used to affect theimplementation of the assay, e.g., such that only cartridge/bay pairswith good connections are processed, and assays associated withcartridge/bay pairs characterized with bad connections are not started.For example, implementations of the disclosed technology are envisionedto produce higher validity rates for assays, which in turn can result inbetter patient care. The disclosed technology can be used in lifescience related fields, the immediate applications include drugscreening, medical diagnostics, environmental monitoring, and pandemicsprevention, etc.

In some embodiments, the disclosed methods include a self-order processevaluation (SOPE) method for assessing the integrity of electricalconnections. In some implementations of the SOPE method, for example, afirst electronic device (e.g., an assay cartridge) is interfaced with asecond electronic device (e.g., analysis device), in which the impedancebetween an electrode or electrodes of the first and the secondelectronic device is measured. The impedance values are ordered fromlowest to highest or highest to lowest (e.g., plotted monotonically),e.g., to form a straight line. The monotonically plotted impedancevalues are then analyzed to see if they fit predefined parameter(s). Forexample, if there is sufficient fit to the predefined parameter(s), themethod allows the electronic device (e.g., cartridge) to be processed;if not, the device is ejected.

In some embodiments, the disclosed methods include a reference-orderprocess evaluation (ROPE) method for assessing the integrity ofelectrical connections. In some implementations of the ROPE method, forexample, a first electronic device (e.g., an assay cartridge) isinterfaced with a second electronic device (e.g., analysis device), inwhich the impedance between an electrode or electrodes of the first andthe second electronic device is measured. The impedance values arereordered according to a predefined order (reference order). Thereordered impedance values are then analyzed to see if they fitpredefined parameter(s). For example, if there is sufficient fit to thepredefined parameter(s), the method allows the electronic device (e.g.,cartridge) to be processed; if not, the device is ejected.

In some embodiments, the disclosed methods include a prior-order processevaluation (POPE) method for assessing the integrity of electricalconnections. In some implementations of the POPE method, for example, afirst electronic device (e.g., an assay cartridge) is interfaced with asecond electronic device (e.g., analysis device), in which the impedancebetween an electrode or electrodes of the first and the secondelectronic device is measured. In some implementations of the POPEmethod, the impedance values are not reordered. The measured impedancevalues are compared to prior impedance values obtained from a previousqualified run of the electronic device, e.g., such as the last qualified(valid) run of a previous cartridge on that particular bay. For example,if the measured impedance values from the first electronic device (e.g.,cartridge's PCB) match or are within a tolerable threshold, thecartridge is processed; if not, the cartridge is ejected. In someimplementations of the POPE method, the impedance values are ordered.For example, R², RFT and EFT values processed from the run can becompared to prior R², RFT and EFT values from a previous run, e.g., thelast qualified (valid) run on that bay. In such implementations, if theR², RFT or EFT values of the first electronic device match a set ofprior R², RFT or EFT obtained from a previously successful run, or arewithin a tolerable threshold, the device is processed; if not, thedevice may be ejected.

In these examples, the SOPE method measures and reorganizes the workingimpedance values monotonically, and the reorganized values are evaluatedto determine the integrity of electrical connections. The ROPE methodmeasures and reorganizes working impedance values according to areference order (RO), and the reorganized values are evaluated todetermine the integrity of electrical connections. The POPE methodmeasures working impedance values and compares them to a reference(e.g., such as prior impedance values obtained from a previous qualifiedrun), and, based on the comparison the device is determined to pass orfail and/or the working impedance values are re-ordered and comparesthem to a reference and subsequently determined to pass or fail.

The example SOPE, ROPE and POPE methods may be implemented using anautomated electrochemical detection assay device to characterize theimpedance of electrical connections corresponding to an electrode of anassay sample cartridge and an electrode of an assay processing bay of aninstrument bank. For example, the assay sample cartridge may be anydevice comprising electrodes. Some example embodiments of the cartridgeinclude those disclosed in U.S. Pat. Nos. 9,498,778 and 9,957,553. Oneexample is shown in FIG. 20 of U.S. Pat. No. 9,957,553, which shows aschematic top perspective view of a cartridge that can be used inimplementations of the disclosed SOPE, ROPE and POPE methods. Anotherexample is shown in FIG. 1 of U.S. Pat. No. 9,498,778, which shows aschematic top perspective view of a cartridge that can be used inimplementations of the disclosed SOPE, ROPE and POPE methods. FIG. 31Bof this application shows a connector board assembly, FIG. 31C of thisapplication shows a connector board assembly with a transparent assaycartridge FIG. 31D of this application shows a connector board assemblywith an assay cartridge over the top.

Similarly, for example, the analysis device, also referred to as a“working device,” can be any instrument that processes the cartridgePCB, such as an instrument bay. Some example embodiments of theinstrument bays as a “working device” include those disclosed in U.S.Pat. Nos. 9,498,778 and 9,957,553. An example is shown in FIGS. 31A and31B of U.S. Pat. No. 9,957,553, which shows a front and side view of theinstrument that can be used in implementations of the disclosed SOPE,ROPE and POPE methods. In these examples, the cartridge is loaded into a“bay.” Each instrument can comprise more than one bay. The bay providesthe electrical connection between the instrument and cartridge. Theseelectrode connectors connecting the cartridge PCB and the working deviceare referred to as connection circuitry. A circuit corresponds to thecontacts between the cartridge and bay. For example, a circuit istypically formed by two electrodes/pads on the cartridge and twoelectrodes on a bay form a circuit. But, a circuit can be formed betweenthree electrodes, either two on the cartridge and one on the bay or oneon the cartridge and two on the bay. Thus, a circuit requires at least 3electrodes. One electrode/pad on the cartridge is always the same andone in unique, the unique electrode/pad is assigned the impedance value.Thus, no matter what electrode/pad (1, 2, 3, etc.) is being tested onthe cartridge the current is also run though the same electrode/pad onthe cartridge (pad 137).

The bays may or may not have been manufactured according to the sameprotocol. For example, it was observed that bays manufactured with evenslight variations have very different abilities to properly connect tocartridges.

As such, before a cartridge is processed (e.g., a sample is assayed fora target analyte), it is pre-tested to make sure that there are noelectrical opens or shorts, i.e., that the cartridge PCB properlyconnect to the electrodes in the instrument. This is referred to as apreflight test. If even one electrode on the PCB is not connected, theability of the cartridge to give a valid result is hampered. Therefore,ensuring that all the electrodes on the PCB are connected to the bay isa critical step in achieving reliable, high-speed signaling. However,detection of an open or shorted electrode is not readily achieved usingconventional capacitive opens or impedance measurement techniquesbecause, as discussed above, bay-to bay variability can effectively maskthe open/shorted connections or call open/shorted connections good whenthey are not.

These and other shortcomings to operate a device with two interfacingcircuits, particularly for conducting a test with an analysis device,would benefit from data processing techniques, like those disclosed, toconfirm the electric connection of the two interfacing circuits. Thedisclosed techniques can be especially beneficial when there is devicevariability, PCB variability and/or measurement variability. Moreover,the disclosed techniques provide additional advantages in the capabilityto be applied across a variety of devices, circuits (e.g., PCBs) withoutmodifying or adding any physical components to the two interfacingcircuits, such as between an instrument bay and a test cartridge.

Accordingly, provided are enhanced apparatuses, systems and methods fortesting the integrity of a connection between, for example, an electrodeon a cartridge PCB and a working device. Example implementations ofsystems and methods are disclosed herein for determining whetherconnection pins of a component of the assembly (instrument) are properlyconnected to the circuit assembly (PCB).

Example Systems for Assessing Electrical Connection Integrity

Example embodiments of SOPE, ROPE and POPE systems and methods aredescribed generally and with respect to specific examples ofinstrumentation and techniques in various implementations.

Example data and results of example implementations of the disclosedsystems and methods are shown in FIGS. 1-17, which are discussed infurther detail later in this disclosure.

FIGS. 18A and 18B show diagrams of example embodiments of a system 1800Aand 1800B, respectively, for assessing electrical integrity betweeninterfacing devices, such as a PCB of a cartridge connected to a circuitof an analytical instrument (e.g., “working device” or “workinginstrument”). The system 1800A shown in FIG. 18A is an example where thesystem is resident on the working device, labeled 1801, to measure andprocess working impedance value or values (WIV) in implementations ofthe SOPE, ROPE or POPE methods. A working impedance value is theimpedance value obtained from the circuit connecting a first electronicdevice having electrical connections interfaced to correspondingelectrical connections of a second electronic device, e.g., such as theimpedance values obtained for electrodes on a PCB of an assay cartridgethat is inserted into a bay of an assay processing device. The system1800B shown in FIG. 18B is an example where a portion of the system isresident on a remote device 1803 and on the working device, labeled1802, which are in data communication with one another to measure andprocess WIV(s) in implementations of the SOPE, ROPE or POPE methods.

The diagrams of FIGS. 18A and 18B show example architectures of therespective systems 1800A and 1800B for assessing an electricalconnection between interfacing circuits. The architecture includesvarious software and hardware modules organized and operable to executean assessment of the electrical connections between the interfacingdevices. The software modules can include a computer program havinginstructions (e.g., code) for executing the data processing steps of theparticular software module. The software modules can be embodied as partof a software application stored in memory of one or both of theinterfacing devices. Similarly, in some embodiments, for example, thesoftware modules can be embodied as part of a data processing systemresident on cloud computer(s) that are in communication with the workinginstrument. In some embodiments, the software modules can be embodied aspart of the software app and the data processing system in the cloud,e.g., in which some or all of the modules of the software architectureare shared or divided among the app and the data processing system.Example embodiments including hardware modules of the systems 1800A and1800B are typically resident of the working instrument, but may also beresident of the other device, such as a test cartridge.

In various embodiments, the systems 1800A and 1800B include analysismodule 1808 configured to analyze measured impedance values acquiredfrom an impedance module 1809 operable to measure impedance valuesacross electrodes interfaced between the two circuits of two devices,for example, the PCB of a cartridge and interfacing connections of theworking instrument (working device 1801 or 1802). In someimplementations, the analysis module 1808 is configured to re-order theimpedance values, exclude impedance values from certain electrodes,adjust the index of impedance values and/or determine an integrity statefor the electrical connection interface, which can include producing apass/fail output for some or each electrode or for the cartridge as awhole. The analysis module 1808 may also be referred to as a “memoryprocessor” of the systems 1800A and 1800B. In some embodiments, theanalysis module 1808 includes a pattern module 1807 configured toanalyze the measured impedance values. In some implementations, thepattern module 1807 assigns each impedance value a first location for adata block sequence, re-orders the impedance values (e.g., creating anew data block for the particular impedance value associated with aparticular electrode), and may exclude impedance values and/or adjustthe index of impedance values. In some embodiments, the analysis module1808 includes a qualifier module 1806 configured to qualify theimpedance data. The qualifier module 1806 may also be referred to as apass/fail module for certain implementations.

The systems 1800A and 1800B include controller module 1805 resident onthe working instrument, e.g., working device 1801 and 1802,respectively, configured to control one or more functions of the workinginstrument, respectively, e.g., such as eject the cartridge insertedinto a bay of the working instrument. The systems 1800A and 1800Binclude data processing module 1804 resident on the working instrument,e.g., working device 1801 and 1802, respectively, configured to controldata processing of the circuit assembly interfaced with the workinginstrument, such as executing control signals to the PCB of the assaycartridge to implement the assay. The systems 1800A and 1800B includeimpedance module 1809 resident on the working instrument, e.g., workingdevice 1801 and 1802, respectively.

In some embodiments, the impedance module 1809 includes a signalgenerator (not shown) and an impedance measurement apparatus (notshown). In implementations, for example, the signal generator generatesand emits a current pulse or a sequence of current pulses. The impedancemeasurement apparatus measures the electrical signal and determines theimpedance value (working impedance value) at each electrode (discussedin more detail below). The impedance module 1809 receives an input datastream comprising at least one data block. In some cases, for example,the data block is a WIV for a particular electrode (where the electrodesfrom the assay cartridge and assay device form a circuit) of thecartridge PCB; whereas in other cases, for example, the data blockincludes another data type, such as current, voltage, time, weight,brightness, distance or combinations thereof associated with theparticular electrode of the cartridge PCB. Once the impedance module1809 obtains an impedance measurement for each electrode it sends thedata block (e.g., WIV and/or other data type associated with aparticular measured electrode) to the analysis module 1808. For example,the impedance module 1809 obtains the impedance measurement values whenthe cartridge PCB interfaces with the cartridge PCB interface 1811 ofthe working device 1801 or 1802, and the signal generator applies anelectrical signal to the cartridge circuit board through the PCBinterface 1811.

The analysis module 1808 may be included in the working device 1801, asshown in FIG. 18A, or the analysis module 1808 may be included in theremote device 1803, as shown in FIG. 18B. In implementations of thesystem 1800B where the analysis module 1808 is on the remote device1803, the data obtained by the impedance module 1809 is sent to theremote device 1803 via a communication module 1812A of the workingdevice 1802 and is received by the remote device 1803 via acommunication module 1812B. The data received at the remote device 1803is provided to the analysis module 1808 for data analysis in accordancewith the SOPE, ROPE or POPE methods. The communication module, e.g.,communication modules 1812A and 1812B, can include a wired communicationsystem (e.g., such as ethernet, cable network, or other) or a wirelesscommunication system (e.g., such as WIFI, LAN, USB, satellite). Thecommunication system may be configured to transmit and receive a signalfrom another communication system.

In some implementations, at the analysis module 1808, the pattern module1807 assigns each impedance value (e.g., WIV or data block) to a firstlocation in a first data block sequence. In some embodiments, thepattern module 1807 re-orders the data blocks. The re-ordered datablocks create a new (second) data block in a new (second) data blocksequence. The pattern module 1807 then sends the new data block sequenceto the qualifier module 1806. The qualifier module 1806 can evaluatewhether the data is within acceptable thresholds. In someimplementations, the qualifier module 1806 may form an affinity arraysuch that each element in the affinity array comprises an affinitynumber based on one or more quality of the fit (QOF) parameters. Forexample, if the QOF parameters (also referred to as the qualityfactor(s) or QOF factor(s)) are not within acceptable thresholds, thequalifier module 1806 sends a fail signal to the controller module 1805to command the working instrument to eject the cartridge. Alternatively,for example, if the QOF parameters are within acceptable thresholds, thequalifier module 1806 sends a pass signal to the data processing module1804 to process the cartridge. Similarly, if the analysis module 1808 ison the remote device 1803, e.g., of system 1800B, the qualifier module1806 sends the output signal to the working device 1802 via acommunication module 1812B to communication module 1812A, which istransferred to the controller 1805 if a fail signal or to the dataprocessing module 1804 if a pass signal.

FIG. 18C shows a diagram of an example embodiment of the data processingmodule 1804. The data processing module 1804 includes a processor toprocess data, a memory in communication with the processor to storedata, and an input/output unit (I/O) to interface the processor and/ormemory to other modules, units or devices of the system 1800A or 1800Bor other devices. In some examples, the processor can include, but isnot limited to, a microprocessor, a microcontroller, a complexinstruction set computing (CISC) microprocessor, a reduced instructionset computing (RISC) microprocessor, a very long instruction word (VLIW)microprocessor, explicitly parallel instruction computing (EPIC)microprocessor, a graphics processor, a digital signal processor (DSP),or any other type of processor or processing circuit. The processor caninclude embedded controllers, such as generic or programmable logicdevices or arrays, application specific integrated circuits, single-chipcomputers, smart cards, and the like. In some examples, the memory caninclude and store processor-executable code, which when executed by theprocessor, configures the data processing module 1804 to perform variousoperations, e.g., such as receiving information, commands, and/or data,processing information and data, and transmitting or providinginformation/data to another device. In some implementations, the dataprocessing module 1804 can transmit raw or processed data to a computersystem or communication network accessible via the Internet (referred toas ‘the cloud’) that includes one or more remote computationalprocessing devices (e.g., servers in the cloud).

To support various functions of the data processing module 1804, thememory can store information and data, such as instructions, software,values, images, and other data processed or referenced by the processor.A variety of computer-readable media may be stored in and accessed fromthe memory, such as volatile memory and non-volatile memory, removablestorage and non-removable storage. Computer memory can include anysuitable memory device(s) for storing data and machine-readableinstructions, such as read only memory (ROM), random access memory(RAM), erasable programmable read only memory (EPROM), electricallyerasable programmable read only memory (EEPROM), hard drive, removablemedia drive for handling compact disks (CDs), digital video disks(DVDs), diskettes, magnetic tape cartridges, memory cards, MemorySticks™, and the like; chemical storage; biological storage; and othertypes of data storage.

In some embodiments, for example, the data processing module 1804includes a wireless communications unit (not shown) to receive data fromand/or transmit data to another device. In some implementations, forexample, the wireless communications unit includes a wirelesstransmitter/receiver (Tx/Rx) unit operable to transmit and/or receivedata with another device via a wireless communication method, e.g.,including, but not limited to, Bluetooth, Bluetooth low energy, Zigbee,IEEE 802.11, Wireless Local Area Network (WLAN), Wireless Personal AreaNetwork (WPAN), Wireless Wide Area Network (WWAN), WiMAX, IEEE 802.16(Worldwide Interoperability for Microwave Access (WiMAX)), 3G/4G/5G/LTEcellular communication methods, NFC (Near Field Communication), andparallel interfaces.

The I/O of the data processing module 1804 can interface the dataprocessing module 1804 with the wireless communications unit and/or awired communication component of the systems 1800A and 1800B to utilizevarious types of wireless or wired interfaces compatible with typicaldata communication standards. The I/O of the data processing module 1804can also interface with other external interfaces, sources of datastorage, and/or visual or audio display devices, etc. For example, thesystems 1800A and 1800B can be configured to be in data communicationwith a visual display and/or additional audio displays (e.g., speakers)of other devices, via the I/O, to provide a visual display, an audiodisplay, and/or other sensory display, respectively.

Machine-readable instructions stored on any of the above-mentionedstorage media are executable by the processor of the data processingmodule 1804. For example, a computer program may comprisemachine-readable instructions capable of encoding according to thedisclosed embodiments. In some embodiments, a computer program may beincluded on a CD-ROM and loaded from the CD-ROM to a hard drive innon-volatile memory. Example encoding techniques include modular andflexible in terms of usage in the form of a “distributed configurablearchitecture”. As a result, portions of the analysis module 1807 may beplaced at different points of a network, for example, depending on themodel chosen. For example, the analysis module 1807 can be deployed in aserver and the predefined parameters or QOF parameters streamed overfrom a client to the server and back, respectively. The analysis module1807 can also be placed on each client, with the database managementcentralized. Such flexibility allows faster deployment to provide acost-effective solution to changing business needs.

Example Methods for Assessing Electrical Connection Integrity

FIG. 18D shows a diagram of an example method 1815 for assessingelectrical connection integrity of interfacing electronic devices. Themethod 1815 includes a process 1810 to establish electrical connectionbetween a first electronic device and a second electronic device. Forexample, in some implementations, the process 1810 can include loadingan assay cartridge into an instrument bay of an automatedelectrochemical detection system such that the PCB of the assaycartridge is in electrical contact with an electrical circuit of theinstrument bay. The method 1815 includes a process 1820 to measure anelectrical signal to determine an impedance value for one or moreelectrical connection interfaces between the first and second electronicdevices. For example, in some implementations, the process 1820 caninclude measuring one or multiple impedance values for some or eachelectrode of the cartridge PCB connected with electrodes on theinstrument bay. The method 1815 includes a process 1830 to analyze theimpedance value to evaluate the integrity of electrical connectivitybetween the first and second electronic devices, and determine a commandfor operating or terminating a procedure using the first and secondelectronic devices. For example, in some implementations, the process1830 can include assigning the impedance values into data blocks basedon the electrode to which the values were measured or obtained;conducting an organization and/or analysis of the data blocks inaccordance with the analysis processing techniques of the SOPE, ROPEand/or POPE methods, described below; determine the quality of theanalyzed data indicative of the integrity of the electrical connectionsbetween the cartridge PCB and the circuit of the instrument bay; andgenerating a command for actuating a function of the detection system.The method 1815 includes a process 1840 to actuate one or both of thefirst and the second electronic device in accordance with the determinedcommand. For example, in some implementations, the process 1840 caninclude executing the assay when the integrity of electrical connectionsis determined to be of an acceptable standard, or ejecting the assaycartridge from the instrument bay when they are determined to be of anunacceptable standard.

Example implementations of the described methods can result in anincreased rate of cartridges ejected from the analysis device, which isreferred to as “do not start” (DNS) errors or DNS failures. Even thoughthe DNS error rate increases, the system failure rate (e.g., falsenegatives and invalids) should decrease because bad cartridges and/orcartridges with poor connections to the analysis device are notprocessed. Moreover, it is incredibly challenging to increase validityrates when validity rates are already very high, e.g., 95% or higher.Notably, increasing the validity rate of existing, FDA approved assaysystems, such as GenMark's ePlex® system, for example, is extremelychallenging because any increase to the validity rate must be achievedwithout any changes to the cartridge or assay system components. It istherefore unexpected that increasing the DNS failure rate can cause anincrease in the validity rate.

FIG. 18E shows a diagram of an example embodiment of a method 1831 foranalyzing impedance values to evaluate a quality factor of electricalconnection between the first electronic device and the second electronicdevice. In some implementations, for example, the method 1831 can beimplemented at the process 1830 of the method 1815. The method 1831includes a process 1832 to assign the one or multiple impedance valuesinto data blocks, in which a data block includes the impedance value (orvalues) that corresponds to the particular electrode circuit associatedwith the impedance value (or values). The method 1831 includes a process1834 to organize the data blocks into a sequence. The method 1831includes a process 1836 to determine the quality factor of theelectrical connection by calculating one, two or more parametersassociated with the sequence of the data blocks and evaluating the one,two or more parameters each to a predetermined threshold value orthreshold range. In some implementations of the process 1834, the datablocks are organized by reordering the data blocks into a monotonicalsequence, which can include a lowest-to-highest monotonical sequence ora highest-to-lowest monotonical sequence. In some implementations of theprocess 1834, the data blocks are organized by reordering the datablocks based on a predetermined reference order (RO), which in somecases creates a monotonic sequence of the reordered data blocks and onother cases does not. In some embodiments of the method 1831, prior tothe process 1834, the method includes comparing the impedance values toprior impedance values obtained from one or more previous preflighttests using the cartridge bay of the assay processing device, and theprocess 1834 can include organizing the data blocks by reordering thedata blocks based on a prior reference order (PRO) at least partiallydetermined by an average of prior valid runs of prior assay cartridges.In some implementations of the method 1831, the one, two or moreparameters include any combination of the following: a correlationcoefficient (R²), a scaled error of fit for an electrode fit test (EFT),a standard error of fit for a run fit test (RFT), and a tolerancedifference value includes a difference of an R² associated with adifferent assay cartridge and the R² associated with the assaycartridge, or a difference of an RFT associated with a different assaycartridge and the RFT associated with the assay cartridge.

Example embodiments of the SOPE, ROPE and POPE including techniques foridentifying expected order of electrodes.

Self-Order Process Evaluation (SOPE) Method

In some embodiments of the method 1815, a self-order process evaluation(SOPE) method is implemented at the process 1830 to determine theworking impedance values and organize them in a monotonic order, uponwhich the organized data are examined according to statisticaltechniques to determine the integrity of the electrical connections. TheSOPE method can be implemented at the analysis module 1808, includingthe pattern module 1807 and the qualifier module 1806.

In determining the working impedance values, the measured impedancevalues are assigned to a data block associated specifically to anelectrode. For example, in a PCB having five electrodes, the analysismodule 1808 assigns the one or more measured WIVs measured for theelectrode-1 to a first data block, assigns the one or more measured WIVsmeasured for the electrode-2 to a second data block, and so forth. Inexample implementations when one or more WIVs are measured at anelectrode circuit, the analysis module 1808 can organize them into anarray of values, which may also be processed to consolidate, select, oraverage values for remaining analysis processes of the SOPE method. Suchprocessing may also be implemented for additional data types associatedwith the electrode, e.g., voltage data, current data, temperature data,etc. Each data block includes (1) one or more data elements associateddirectly with the electrical connection point (e.g., circuit) betweenthe first and second electronic devices (e.g., electrode of a cartridgePCB and electrodes of the analysis device), and (2) an index number,e.g., so that the data blocks may be referenced based on anyorganization or reordering scheme.

In determining the order of the data blocks, the pattern module 1807compares each data block to one another and assigns each data block afirst location in a first data block sequence. The data blocks are thenreordered from lowest WIV to highest WIV (i.e., plotted monotonically),or from highest WIV to lowest WIV (i.e., plotted monotonically), to forma new data block sequence (also referred to as a reordered WIV orR-WIV). In some implementations, each data block of the first data blocksequence is assigned a second location identifier for the second (new)data block sequence also referred to as organized data blocks ororganized data block sequence. In some implementations, a second (new)set of data blocks is created to store the data in the first set of datablocks, which is organized monotonically in the second data blocksequence. Each new data block is given a second location as a functionof the re-order. For example, in implementations of the detection systemusing the assay cartridges, preferably the second location for each datablock identifies the location of the corresponding electrode on the PCBof the cartridge and electrode on the analysis device. The reordereddata blocks (R-WIV) is further analyzed to evaluate key parameters.Notably, in the SOPE method, the data blocks (of WIVs associated withthe particular electrodes) are not re-ordered according to a predefinedpattern, but rather the reordering pattern is based on the determinedWIV values themselves.

In some implementations, the new data block sequence produces a straightline based on the monotonical plotting of WIVs. In some implementationsof the SOPE method, for example, prior to rearranging or afterrearranging, certain data blocks can be excluded. As discussed in moredetail below, data blocks may be excluded because (1) the electrode ishighly variable run-to-run or (2) the electrode's impedance measurementis too high or too low.

In some implementations, the new data block may exclude some electrodesor adjust the fit to improve linearity or combinations thereof. In someimplementations, certain data blocks are excluded and the index of eachordered electrode is adjusted.

In evaluating the integrity of the electrical connections, the organizeddata blocks are provided to the qualifier module 1806 (e.g., alsoreferred to as the pass/fail module for some implementations) to qualifythe new data blocks in the organized data blocks sequence. In someimplementations, for example, to qualify the new data blocks, theorganized data blocks sequence is analyzed according to one parameter:correlation coefficient (R²), EFT, RFT, intercept of the fitted line orslope of the fitted line. In some implementations, for example, toqualify the new data blocks, the organized data blocks sequence isanalyzed according to two parameters: correlation coefficient (R²) andan electrode fit test (EFT). In some embodiments, the organized datablocks sequence is analyzed according to a plurality of parameters:correlation coefficient (R²), EFT, RFT, intercept of the fitted lineand/or slope of the fitted line.

Equation 1 is shown for the correlation coefficient, R²:

$\begin{matrix}{{{Correl}\left( {X,Y} \right)} = \frac{\sum{\left( {x - \overset{\_}{x}} \right)\left( {y - \overset{\_}{y}} \right)}}{\sqrt{\sum{\left( {x - \overset{\_}{x}} \right)^{2}{\sum\left( {y - \overset{\_}{y}} \right)^{2}}}}}} & (1)\end{matrix}$where x and y are the sample means AVERAGE(array1) and AVERAGE(array2),and where X corresponds to the index and Y corresponds to the impedancemeasurements.

Equation 2 is shown for the standard error of the predicted fit (RFT):

$\begin{matrix}\sqrt{\frac{1}{\left( {n - 2} \right)}\left\lbrack {{\sum\left( {y - \overset{\_}{y}} \right)^{2}} - \frac{\left\lbrack {\sum{\left( {x - \overset{\_}{x}} \right)\left( {y - \overset{\_}{y}} \right)}} \right\rbrack^{2}}{\sum\left( {x - \overset{\_}{x}} \right)^{2}}} \right\rbrack} & (2)\end{matrix}$where x and y are the sample means AVERAGE(known_x's) andAVERAGE(known_y's), and n is the sample size. x and y are the index andimpedance for each point. “x-bar” and “y-bar” are the averages of each;and the sums go over all the points.

Equation 3 is shown for the scaled error of the linear fit for eachelectrode (EFT).EFT=scaled error=(((index*slope)+intercept)−impedance)/RFT  (3)

In some example implementations of the SOPE method, the organized datablocks sequence is analyzed according to two parameters: correlationcoefficient (R²) and an electrode fit test (EFT). For the firstparameter, for example, the impedance values in each data block areexamined collectively in their organized data blocks sequence todetermine the correlation coefficient (R²). Preferably, for example, R²is about 1. In some implementations, acceptable R² values may be betweenabout 0.8 and 1, or at least about 0.9, or between 0.98 to 1. For thesecond parameter, for example, each individual electrode is examinedindividually to determine the scaled error of the fit, referred to asthe “electrode fit test” or EFT. Preferably, for example, the EFT foreach electrode is less than about 4 (for an open). Preferably, forexample, the EFT for each electrode is greater than about −4 (for ashort). Preferably, for example, the EFT for each electrode is between−4 and +4 (for an open and short). Preferably, for example, the EFT foreach electrode is less than about 3 (for an open). Preferably, forexample, the EFT for each electrode is between about 0 and less than 4(for an open). Preferably, for example, the EFT for each electrode isbetween about 0 and less than 5 (for an open). Preferably, for example,the EFT for each electrode is greater than about −3. Preferably, forexample, the EFT for each electrode is between about 0 and greater than−4 for short. In some implementations, the EFT for each electrode isbetween about 0 and greater than −5 for short. Using the two evaluatedparameters, the SOPE method can determine a command for operating theelectronic devices.

In some implementations, if any one parameter does not meet apredetermined threshold the cartridge fails the preflight test and isejected.

In some implementations, if R² is not between 0.95 and 1, then thepreflight test fails and the cartridge is ejected. In someimplementations, if any EFT is too far from the fitted prediction (e.g.,has a value greater than 4 (open) or less than −4 (short), the preflighttest fails and the cartridge is ejected. In some implementations, ifboth the R² is not between 0.95 and 1 and if any EFT has a value greaterthan 4 (open) or less than −4 (short), the preflight test fails and thecartridge is ejected.

In some implementations, if R² is between 0.95 and 1, the preflight testpasses and the cartridge is processed. In some implementations, if allof the EFTs have a value less than 4 (open) or greater than −4 (short)the preflight test passes and the cartridge is processed. In someimplementations, if both the R² is between 0.95 and 1 and all of theEFTs have a value less than 4 (open) or greater than −4 (short), thepreflight test passes and the cartridge is processed.

For example, by first plotting impedance values monotonically and/orexcluding some electrodes and/or adjusting the fit to improve linearity,and second measuring the R² to ensure it is between 0.8 and 1 and/ormeasuring the EFT to ensure it is between 0 and less than 5, e.g.,preferably between 0 and less than 4 (open) or between 0 and greaterthan −4 (short), a proper connection between a bay and PCB can beidentified. By first plotting impedance values monotonically and/orexcluding some electrodes and/or adjusting the fit to improve linearity,and second measuring the R² to ensure it is between 0.8 and 1 and/ormeasuring the EFT to ensure it is between 0 and less than 5, e.g.,preferably between 0 and less than 4 (open) or between 0 and greaterthan −4 (short) an improper connection between a bay and PCB can beidentified.

In some implementations, the qualifier module 1806 is configured to passor fail the cartridge based on the evaluated, reorganized data blocks.For example, in the case of a fail, the qualifier module 1806 producesan output indicating that the cartridge and bay are not properlyconnected, e.g., producing an error message sent to the controllermodule 1805, from which the controller module 1805 ejects the cartridge.For example, in the case of a pass, the qualifier module 1806 producesan output indicating that the cartridge and bay are properly connected,e.g., producing a pass message sent to the data processing module 1804,e.g., which can be resident on the analysis instrument or remoteinstrument, to initiate processing of the cartridge.

In some embodiments, the analysis module 1808 including the patternmodule 1807 and qualifier module 1806 are resident in an instrument bankof the example automated electrochemical detection system, whereas insome embodiments, the analysis module 1808 is resident in the basestation. In some embodiments, the analysis module 1808 is resident in aremote instrument in data communication with the working instrument. Insome embodiments, portions of the analysis module 1808 is resident in acombination of any of the instrument bank, base station or remoteinstrument.

Reference-Order Process Evaluation (ROPE) Method

In some embodiments of the method 1815, a reference-order processevaluation (ROPE) method is implemented at the process 1830 to determinethe working impedance values and organize them in a particular orderbased on a reference order, upon which the reference-organized data areexamined according to statistical techniques to determine the integrityof the electrical connections. The ROPE method can be implemented at theanalysis module 1808, including the pattern module 1807 and thequalifier module 1806.

In the above described SOPE method, the re-ordered impedance values arebased on the impedance values obtained from the cartridge PCB beingprocessed, i.e., the WIV. In contrast, the ROPE method uses reorderedimpedance values based on one or more reference orders (RO). Forexample, the ROPE method can include a review of internal and externaldata that define a pattern. The pattern can be the predeterminedexpected sequence of electrodes that yields a monotonic plot ofimpedance values.

For example, the ROPE method is designed to identify electricalconnection integrity issues observed for cartridge-working deviceinterfaces where different iterations of the connector board (e.g.,different designs, different suppliers, different material orcombinations thereof) showed different impedance patterns when plottedmonotonically; however, the monotonic plots proved sufficientlyconsistent across multiple connector boards to allow each type ofconnector board (type 1, type 2, type 3 . . . type n) to use the samemonotonic plot, i.e., same order of electrodes. Thus, the ROPE methodrelies on impedance values following a consistent pattern run-to-run.The ROPE method fits the current impedance data to a pattern orpatterns, thereby reducing the effect of run-to-run variability.

This characterization of bays helps identify different bay types thathave different expected patterns. The ROPE method may identify whichgroup a bay belongs to by applying the different patterns and selectingthe pattern that gives the best fit to the working impedancemeasurements.

In determining the working impedance values, the measured impedancevalues are assigned to a first data block associated specifically to anelectrode circuit. This is similar, for example, to what is describedabove with respect to the SOPE method. The analysis module 1808 assignsthe one or more measured WIVs measured at each electrode to acorresponding data block. For example, in example implementations whenone or more WIVs are measured at an electrode circuit, the analysismodule 1808 can organize them into an array of values, which may also beprocessed to consolidate, select, or average values for remaininganalysis processes of the ROPE method. Such processing may also beimplemented for additional data types associated with the electrode,e.g., voltage data, current data, temperature data, etc.

In determining the order of the data blocks, the pattern module 1807assigns each data block a first location in a first data block sequence.The pattern module 1807 then reorders the WIVs to match a referenceorder (RO) to form a new data block sequence (also referred to as areference-ordered WIV sequence or RO-WIV sequence or ordered data blocksequence or second data block sequence). In some embodiments, the RO canbe the order of data blocks defined by the SOPE method. For example, themethod 1810 can implement the process 1830 associated with the SOPEmethod to determine an RO for subsequent implementations of the process1830 in accordance with the ROPE method. In some embodiments, thepredefined order is an order in which the impedance values are orderedfrom lowest to highest to form a straight line (i.e., plottedmonotonically) for another cartridge/bay connection. Each new data blockis given a second location as a function of the reorganizing. If morethan one RO is known, the first sequence of data blocks (e.g., thedetermined WIV from the process 1820) can be reordered to match some oreach of the previous determined ROs. For example, the reordering of thedata blocks to match more than one RO can produce a plurality of new,reordered data block sequences. Each reordered data block (new datablock 1, new data block 2, new data block 3 . . . new data block n) inthe new data block sequence is given a new location as a function of thereorganizing (new location 1, new location 2, new location 3 . . . newlocation n).

In some implementations, prior to rearranging or after rearranging,certain data blocks can be excluded. As discussed below, data blocks maybe excluded because (1) the electrode is highly variable run-to-run or(2) the electrode's impedance measurement is too high or too low. Insome implementations, the index of each ordered electrode is adjusted.As such, the new data block may exclude some electrodes or adjust thefit to improve linearity or combinations thereof. In someimplementations, the new data block sequence implemented the ROPE methodresults in a straight line (i.e., plotted monotonically). In otherimplementations, the ROPE method does not result in a straight line. Thegoal is to find the RO such that the WIVs when reordered are plottedmonotonically.

In establishing the RO, the pattern module 1807 of the analysis module1808 is used to generate the RO, which can be established prior to theprocess 1810 (e.g., loading the cartridge into the instrument). Forexample, different iterations of the connector boards (e.g., differentdesigns, different suppliers) showed different impedance patterns;however, the pass/fail limits proved sufficiently consistent across themto allow each pattern to use the same pair of limits. ROs can be basedon recognizing these patterns at the pattern module 1807.

In some implementations of the ROPE method, the RO is based on priorruns performed on previous working devices that is the same type as theworking device used in the method, which is referred to as the ROestablishment device. In some implementations, for example, the ROestablishment device is a device(s) in the field, a test device(s) orcombinations thereof. In some implementations, for example, the ROestablishment device has the same design, same supplier, same materialor combinations thereof as the working device. In some implementations,for example, the RO is based on prior runs performed on the workingdevice.

In some implementations, for example, the RO is based on a cartridgethat ran in a RO establishment device that resulted in a validrun/result, e.g., it did not have a preflight test error, operationerror, or a detection error. In some implementations, for example, theRO is based on a cartridge that ran in a RO establishment device thatresulted in an invalid run/result but not because of a connection error,e.g., it did not have a preflight test error.

The RO establishment device(s) can generate a RO working impedance value(RO-WIV) or RO data block. The expected order (EO) or Reference Order(RO) may be generated from the RO-WIV. In some implementations, the ROis created from the RO-WIV plotted monotonically. In someimplementations, for a plurality of working impedance values from aplurality of runs using the RO establishment device(s), the RO iscreated from the average impedance value at each electrode circuit fromprior RO establishment device(s) reordered monotonically. In someimplementations, the RO is created from the average of the highest andlowest impedance value at each electrode circuit from prior ROestablishment device(s) reordered monotonically. In someimplementations, the RO is created from the mean impedance value at eachelectrode circuit from prior RO establishment device(s) reorderedmonotonically. In some implementations, the RO is created from impedancevalues at each electrode circuit from prior RO establishment device(s)wherein some RO data blocks are excluded. As discussed below, in someexamples, RO data blocks may be excluded because (1) the electrode ishighly variable run-to-run or (2) the electrode's impedance measurementis too high or too low.

In some implementations, the index of each ordered electrode from the ROdata block is adjusted. As such, the new RO data block may exclude someelectrodes or adjust the fit to improve linearity or combinationsthereof. In some embodiments, certain RO data blocks are excluded andthe index of each ordered electrode is adjusted. In someimplementations, the new RO data block is a straight line (i.e., plottedmonotonically).

When applying the RO method, the electrode order (RO) from the ROestablishment device(s) may be applied to the impedance values (e.g.,WIVs) from the working device.

In some embodiments, the ROPE method is based on frequency patterns. Insome implementations, the frequency pattern is generated by taking theaverage impedance value for each electrode across several ROestablishment device runs and ordering them monotonically. The frequencypattern may also exclude some electrodes as discussed above, e.g., suchas excluding electrodes with high variability or excluding electrodeswith high impedance values or low impedance values. The frequencypattern may be adjusted to fit a line.

Each RO that has been determined is applied to each data block. Thus,each data block is re-ordered n times. Specifically, the pattern modulere-orders the WIV to fit the first RO pattern. If more than one ROpattern is available, the WIV is re-ordered again according to each ROpattern and the quality of each fit of each RO-WIV is analyzed. In otherimplementations, the RO-WIV is evaluated and if it passes the cartridgeis processed, if it fails a second RO-WIV is evaluated until thecartridge passes or until no RO-WIV is found that passes and thecartridge is ejected.

After the impedance module 1809 determines the WIV and sends it to thepattern module 1807 of the analysis module 1808, which creates the newdata block(s) based on the RO(s), the pattern module 1807 sends the newdata blocks to qualifier module 1806 (e.g., also referred to as thepass/fail module for some implementations) to qualify the new datablocks in the RO sequence, e.g., evaluating certain parameters of thenew re-ordered data blocks.

Determining the Best Fit Using One or Both of R² and RFT

In some embodiments of the ROPE method, the best first is based on onepredefined parameter. In some embodiments of the ROPE method, the bestfirst is based on two predefined parameters. In some embodiments of theROPE method, the best first is based on a plurality of predefinedparameters.

In some embodiments of the ROPE method, the predefined parameters arethe correlation coefficient (R²), the standard error of the fit calledthe run fit test (RFT), or both. Run Fit Test (RFT) is the standarderror of the linear fit for all the electrodes analyzed.

For the first parameter, for example, the impedance values in each datablock are examined collectively in their data block sequence todetermine the correlation coefficient (R²). Preferably, for example, R²is about 1. In some implementations, acceptable R² values may be betweenabout 0.8 and 1, or at least about 0.9, or between 0.98 to 1. For thesecond parameter, for example, all the electrodes are examinedcollectively to determine the RFT. Preferably, for example, the RFT foreach electrode is less than 30. In some implementations, acceptable RFTfor each electrode is less than 28. In some implementations, acceptableRFT for each electrode is between 10 and 35.

If one RO is available, for example, a best fit includes the new datablock with an R² between 0.98 and 1 or a RFT between 10 and 35 or both.If more than one RO is available, for example, the R², the RFT, or bothare generated for each RO and compared to each other. This may bereferred to as RO-1, RO-2, RO-3 . . . RO-n. This may be referred to asR²-1, R²-2, R²-3 . . . R²-n. This may be referred to as RFT-1, RFT-2,RFT-3 . . . RFT-n.

In some implementations, the best fit means the new data block has thehighest R² or the lowest standard error of the linear fit (RFT), orboth, compared to the new data blocks for each of the other ROsanalyzed. Some examples are described below for determining the bestfit.

In some implementations, the RO pattern with the lowest RFT is used todetermine if the cartridge passes the preflight test. In someimplementations, the RO pattern with the highest R² is used to determineif the cartridge passes the preflight test. In some implementations, theRO pattern with both the lowest RFT and highest R² is used to determineif the cartridge passes the preflight test. In some implementations, theRO pattern with both the highest RFT and lowest R² is used to determineif the cartridge fails the preflight test. In some implementations, ifno RO pattern gives both the lowest RFT and highest R², the method failsthe preflight test. In some implementations, the RO pattern with eitherthe lowest RFT or highest R² is used to determine if the cartridgepasses the preflight test. In some implementations, the RO pattern witheither the highest RFT or lowest R² is used to determine if thecartridge fails the preflight test. In some implementations, if the ROpattern gives an unacceptable RFT but acceptable R², the RO patternfails the preflight test. In some implementations, if the RO patterngives an acceptable RFT but unacceptable R², the RO pattern fails thepreflight test.

In some implementations, the RO-WIV with the lowest RFT is applied todetermine if the cartridge passes the preflight test. In someimplementations, the RO-WIV with the highest R² is applied to determineif the cartridge passes the preflight test. In some implementations, theRO-WIV pattern with both the lowest RFT and highest R² is applied todetermine if the cartridge passes the preflight test. In someimplementations, the RO-WIV pattern with the lowest RFT or highest R² orboth is applied to determine if the cartridge fails the preflight test.In some implementations, if no RO-WIV gives both the lowest RFT andhighest R², the method fails the preflight test. In someimplementations, if the RO-WIV gives an unacceptable RFT but acceptableR², the RO-WIV fails the preflight test. In some implementations, if theR-WIV gives an acceptable RFT but unacceptable R², the RO-WIV fails thepreflight test. In some implementations, the RO-WIV must have both thelowest RFT and highest R², to pass the preflight test.

Requiring both extremes (e.g., lowest RFT and highest R²) to come fromthe same pattern increases the confidence that the method chose thecorrect pattern. Patterns that give nearly identical values might allowfor relaxing this dual requirement. In cases where more than one patternappears acceptable, the pattern with the most number of electrodesanalyzed may be selected. In some implementations, the RO-WIV must haveboth an acceptable RFT and an acceptable R², and at least 100 electrodesto pass the preflight test. In some implementations, the RO-WIV with themost electrodes and an acceptable RFT and acceptable R² is needed topass the pre-flight test.

In some implementations, the qualifier module 1806 is configured to passor fail the assay cartridge based on the evaluated, organized new datablocks. In some implementations, for example, once the best fit usingthe R² and RFT parameters is determined, the cartridge can be furtherevaluated for pass/fail by evaluating each individual electrode todetermine the scaled error of the electrode fit test (EFT). In someembodiments, expected pass/fail criteria for each electrode may begenerated that accounts for acceptable variation in actual measurementvalues recorded for that working electrode. Preferably, for example, theEFT for each electrode is less than about 4 (open) or greater than −4(short). In some implementations, the EFT for each electrode less thanabout 3. In some implementations, the EFT for each electrode is between−5 and 5. The error threshold may differ for different electrodes. Insome implementations, the error threshold is the same for everyelectrode on the cartridge PCB. The RFT fits the data to a line(modeling) and because it looks at all of the electrodes collectively,it's possible that large scaled errors could pass under the RFT test. Incontrast, the EFT analysis is a point-by-point measurement, and shouldidentify if any single electrode circuit is above a threshold.

By plotting impedance values monotonically and excluding some electrodesor adjusting the fit to improve linearity or combinations thereof, aproper connection between a bay and cartridge PCB can be identified.Conversely, by plotting impedance values monotonically and excludingsome electrodes or adjusting the fit to improve linearity orcombinations thereof, an improper connection between a bay and cartridgePCB can be identified.

If the pass/fail module determines that the cartridge and bay are notproperly connected, for example, the qualifier module 1806 produces anerror message sent to the controller module 1805, from which thecontroller module 1805 ejects the cartridge. If the pass/fail moduledetermines that the cartridge and bay are properly connected, forexample, the qualifier module 1806 produces a pass message sent to thedata processing module 1804 to initiate processing of the cartridge.

Prior-Order Process Evaluation (POPE) Method

In some embodiments of the method 1815, a prior-order process evaluation(POPE) method is implemented at the process 1830 to determine theworking impedance values into data blocks and compare them topredetermined values, upon which the working impedance values can bere-organized data and/or are examined according to statisticaltechniques to determine the integrity of the electrical connections. ThePOPE method can be implemented at the analysis module 1808, includingthe pattern module 1807 and the qualifier module 1806.

In determining the working impedance values, the measured impedancevalues are assigned to a data block associated specifically to anelectrode, e.g., which is also referred to as the first data block or acurrent data block or a working data block.

In the POPE method, the pattern module 1807 assigns each data block afirst location in a data block sequence.

In some embodiments of the POPE method, the pattern module 1807 does notreorder the data blocks. Instead, each data block is compared to animpedance value from a prior run or an average of prior runs implementedon the working device. In some implementations, prior to the comparisonof the impedance values to the prior run or average of prior run values,the pattern module 1807 organizes the data blocks into a sequenceassociated with the corresponding electrodes, e.g., such as an electrodenumber or series of operation, and not the impedance values.

In some embodiments of the POPE method, the pattern module 1807 thenreorders the WIVs to match a prior-reference order (PRO) to form a newdata block (also referred to as a prior-reference-ordered WIV orPRO-WIV). Each new data block is given a second location as a functionof the reorganizing. However, in the POPE method, as compared to theROPE method, the POPE method PRO is based on a prior valid run on theworking device. In some implementations, for example, the PRO is basedon an average of 2-100 prior valid runs on the working device.

In some implementations of the POPE method, prior to or after thereorganizing with respect to the prior reference order, certain datablocks can be excluded. For example, data blocks may be excluded because(1) the electrode is highly variable run-to-run or (2) the electrode'simpedance measurement is too high or too low.

In some implementations, the index of each ordered electrode isadjusted. As such, the new data block may exclude some electrodes oradjust the fit to improve linearity or combinations thereof. In someimplementations, the new data block is a straight line (e.g., plottedmonotonically).

After the impedance module 1809 determines the WIV and sends it to thepattern module 1807 of the analysis module 1808, which in someimplementations creates a sequence of new data block(s) based on thePRO(s), the pattern module 1807 sends the data blocks to qualifiermodule 1806 (e.g., also referred to as the pass/fail module for someimplementations) to qualify the data blocks, e.g., evaluating certainparameters of the new data blocks.

In the example embodiments of the POPE method where the data is notre-ordered, the WIV is compared to the prior reference WIV, and if it iswithin a tolerable variance, the cartridge passes or fails.

In some embodiments of the POPE method, the best first is based on onepredefined parameter. In some embodiments of the POPE method, the bestfirst is based on two predefined parameters. In some embodiments of thePOPE method, the best first is based on a plurality of predefinedparameters.

In the example embodiments of the POPE method where the data isre-ordered, determining the best fit is based on tolerable differenceparameters: tolerable difference for the R² and/or RFT and/or EFTbetween a prior run and the present run R² and/or RFT and/or EFT.

For example, the qualifier module 1806 makes the determinations inconsideration of whether the difference between a previous run R² and/orRFT and/or EFT and the present run R² and/or RFT and/or EFT is greaterthan a difference tolerance threshold.

In the example embodiments of the POPE method where the data isre-ordered, determining the best fit is based on three sets ofparameters: (1) correlation coefficient (R²); (2) standard error of thefit for the run fit test (RFT); and (3) tolerable difference for the R2and/or RFT between a prior run and the present run R² and/or RFT.

For example, the qualifier module 1806 makes the determinations inconsideration of all the impedance values together, e.g., determiningwhether the R² for the present run exceeds the R² threshold; determiningwhether the RFT for the present run exceeds the RFT threshold; and (3)determining whether the difference between a previous run R² and/or RFTand the present run R² and/or RFT is greater than a difference tolerancethreshold.

For the tolerable difference parameter, if the difference is too great,the cartridge fails. As an example, the prior run R² could be 0.98(acceptable) and the current R2 could be 0.92 (acceptable), but becausethe difference between the prior run R² and current R² is greater than0.05, the difference is considered to great and the cartridge fails. Insome implementations, tolerable differences between R² values is between0.0 and 0.4; and intolerable differences between R² values is between0.5-1. In some implementations, tolerable differences between RFT valuesis between 1-5; and intolerable differences between RFT values isbetween 5-28.

In some implementations, once the quality of the fit is determined atthe qualifier module 1806, the cartridge is evaluated for pass/fail byevaluating each individual electrode to determine the scaled error ofthe fit also referred to as the electrode fit test (EFT). In someimplementations, the qualifier module 1806 can then determine if atolerable difference is present between the current value for EFTcompared to the prior run value for EFT. For example, the prior run EFTcould be 1.8 (e.g., acceptable) and the current EFT could be 3.5 (e.g.,acceptable), but because the difference between the prior run EFT andcurrent EFT is greater than 1.5, the difference is considered too greatand the cartridge fails. In some implementations, for example, tolerabledifferences between EFT values is between 0-1.5; and intolerabledifferences between EFT values is between 1.5-4.

Alternatively, the tolerable difference can be determined based on thedifference between the ratio of the current value for R², RFT, or EFTcompared to a goal value (e.g., max or minimum value), compared to theratio of the prior run value for R², RFT, or EFT compared to a goalvalue (max or minimum value). For example, the prior run R² could be0.98/28 (acceptable) and the current R² could be 0.92/28 (acceptable),and because the difference between the prior run R² and current R² isless than 0.05/28, the difference is considered small and the cartridgepasses.

In some implementations, the qualifier module 1806 is configured to passor fail the example assay cartridge based on the evaluated, reorganizeddata blocks. If the pass/fail module determines that the cartridge andbay are not properly connected, for example, a case of a fail, thequalifier module 1806 produces an error message sent to the controllermodule 1805, from which the controller module 1805 ejects the cartridge.If the pass/fail module determines that the cartridge and bay areproperly connected, for example, a case of a pass, the qualifier module1806 produces a pass message sent to the data processing module 1804 toinitiate processing of the cartridge. In some implementations, expectedpass/fail criteria for each electrode may be generated that accounts foracceptable variation in actual measurement values recorded for thatworking electrode. For example, the EFT for each electrode is preferablyless than 4 (open) or greater than −4 (short), where is some examples,the EFT for each electrode is preferably less than 3, where is someexamples, the EFT for each electrode is preferably between 0 and lessthan 5. The error threshold may differ for different electrodes. In someimplementations, the error threshold is the same for every electrode onthe PCB.

Further discussion pertaining to example implementations of theprocesses of the method 1815 and the method 1831 are discussed below,including in relation to the processes of the SOPE, ROPE and POPEmethods.

Measuring Working Impedance

Example embodiments of the process to measure working impedance valuesof an interfaced device, such as a PCB of an assay cartridge andelectronic connections of an assay device, are described below.

Typically, a PCB include a laminate of a conductive material, e.g.,copper, as well as an insulating dielectric substrate. The traces formedby the copper material provide signaling paths for communication betweenthe cartridge PCB and the electronic device on the working instrument.These traces can act like electrical transmission lines.

Impedance is a measure of passive opposition to the flow of currentalong the trace. Impedance includes resistance (to direct current),reactance (to alternating current), inductance and capacitance. Thelength and width of each trace, its proximity to other traces, and thenumber of board layers are among the many factors affecting traceimpedance in PCBs. Generally, wider traces have lower impedances, whereother factors are equal. An impedance mismatch is the discontinuitybetween the impedances of two communicating components, e.g., such asbetween the electrical connections of the cartridge PCB and theinterfacing conductive paths of the working instrument circuit, e.g., aPCB of the working instrument. When an impedance mismatch is present,reflection along the signal trace can occur. The reflected signal willadd to or subtract from the original signal being transmitted betweenthe components, thereby causing a distortion and, possibly, a failure ofthe transmission.

Generally, PCB boards are manufactured to meet certain trace impedances,within some tolerance. Thus, where a 50-ohm PCB is specified, plus orminus fifteen percent, the impedance of all traces on the PCB will bebetween 42.5 and 57.5 ohms. A single PCB can simultaneously includetraces of different widths, such as 50-ohm traces and 60-ohm traces, forexample. This enables signal groups with different impedancerequirements to simultaneously occupy the PCB. A memory interface mayhave a 60-ohm impedance requirement while a processor interface, locatedon the same PCB, has a 50-ohm impedance requirement.

Despite having a board with a known trace impedance, it is important toassess and qualify the connection between two interfacing PCB boards.Qualifying the connection between two interfacing PCBs improves signalintegrity, reduces reflections and ringing along the trace that mayadversely affect system performance.

Applicants have discovered that the variation of trace impedance betweentwo working instruments can be significant such that valid cartridgesare discarded leading to waste and/or invalid cartridges are processedleading to false negatives/invalids. In particular, for example, thesame electrode from a cartridge on two different working instruments mayhave a variation in the trace impedance of about 5%, or 10% or 20% or30% or 40% or 50% between 1-50% in various implementations.

In some implementations, the working device is programmed to send avoltage of a defined size and frequency to the cartridge PCB. Theworking device measures the circuit resistance (e.g., real impedancecomponent) and capacitance and inductance of each electrode on thecartridge. The results depend on circuit parameters, particularly open,closed or shorts.

In some embodiments of the disclosed methods for assessing electricalconnection integrity, the process for measuring impedance is achievedby: (1) applying a voltage between or among two PCB electrodes at agiven frequency (or multiple frequencies, or having specific voltagewaveform) and monitoring the electrical current through said electrodesat the frequency (or multiple frequencies, or having specific waveform),dividing the voltage amplitude value by the current amplitude value toderive the impedance value; and/or (2) applying an electric current of asingle frequency component (or multiple frequencies or having specificcurrent wave form) through said electrodes and monitoring the voltageresulted between or among said electrodes at the frequency (or multiplefrequencies, or having specific waveform), dividing the voltageamplitude value by the current amplitude value to derive the impedancevalue. Other techniques can also be employed to measure or determineelectric impedance. Note that in the description above regarding“dividing the voltage amplitude value by the current amplitude value toderive the impedance value,” the “division” is done for the values ofcurrent amplitude and voltage amplitude at the same frequencies.

Insofar as conventional printed circuit board design techniques indicatethat the connection of two PCB boards together should work in anacceptable manner, the failure of the components to work together hasgiven rise to the need for determining why the unacceptable errors areoccurring, and, if the cause of the unacceptable errors can bedetermined, providing a connection specific method such that theperformance of the electronic system, such as an automatedelectrochemical detection system connected to a cartridge, is acceptablewithout any design changes to the PCB of either interfaced devices,e.g., an assay cartridge PCB and instrument bay.

In some embodiments of the impedance module 1809, the signal generatoris operable as an impedance signal source that provides an impedancesignal. The impedance module 1809 is coupled to the PCB interface 1811that includes the electrical connection structures of the workinginstrument that electrically connect to the corresponding electricalconnection structures of the cartridge PCB. The signal generator appliesan electrical signal to the cartridge circuit board through the bay PCBinterface location. In some embodiments, the signal generator is part ofthe working device 1801 or 1802 (e.g., instrument bay assembly) and isimplemented as part of the normal functional circuitry of the bayassembly. For example, the signal generator may include amicroprocessor, a microprocessor-based integrated circuit, anoscillator, or an IC supporting Boundary Scan. The signal generatorgenerates the impedance signal at a predetermined frequency. Thepredetermined frequency of the impedance signal is preferablyharmonically unrelated to the frequency of any other signal associatedwith the device. For example, this helps to avoid false detections andfalse integrity indications. An electrical signal path connects theoutput of the signal generator to an electrical connection on the PCBassembly. Preferably, this signal path is the same path that implementsthe normal function of the working device 1801 or 1802 (e.g., instrumentbay of the automated electrochemical detection system) during normaloperation of the circuit assembly/cartridge. The signal generator istherefore able to apply the impedance signal to the electricalconnection without having to probe an electrical signal path or theelectrical connection.

In some embodiments of the impedance module 1809, the impedancemeasurement apparatus, also referred to as an impedance sensor or animpedance detector, is configured to detect the impedance signal fromthe electrical connection. The impedance sensor is positionedproximately near the electrical connection so that the sensor can detectthe amplitude of the impedance signal passing through the electricalconnection.

In conventional impedance detection systems, for example, the detectedamplitude is compared to a threshold value, and the comparison of thedetected amplitude to the threshold value is indicative of the integrityof the electrical connection between two interfacing devices. In otherwords, the comparison indicates whether the electrical signal path isproperly connected between two interfacing devices. But, as discussedabove, comparing the detected impedance amplitude to the thresholdimpedance value results in runs with poor connectivity to pass and runswith good connectivity to fail.

The disclosed systems include an impedance module that provides adetection signal to an analysis module indicating a detected value ofthe impedance signal, e.g., such as the magnitude and/or phase of theimpedance signal.

Analyzing the Detected Impedance Signal

Once the analysis module 1808 has received the detection signal from theimpedance module, the analysis module 1808 analyzes the measuredimpedance values acquired from an impedance module 1809 in accordancewith the SOPE, ROPE and/or POPE methods. For example, in the SOPEmethod, the analysis module 1808 re-orders the WIVs either from highestto lowest WIV values or lowest to highest WIV values. For example, inthe ROPE method, the analysis module 1808 utilizes the pattern module1807 to reorganize the WIVs according to a reference order (RO). Forexample, in the POPE method, the analysis module 1808 does not re-orderthe WIVs and compares the impedance value of each electrode (where theelectrodes from the assay cartridge and assay device form a circuit) toa prior valid run. This comparison (e.g., to a predetermined pattern orprior valid run as compared to a threshold) is an improved indicator ofthe integrity of the electrical connection. The integrity of theelectrical connection is typically considered to be whether theelectrical signal path, such as a wire trace on the printed circuitassembly, is properly connected to the working device.

Assigning and/or Reordering Impedance Values by the Pattern Module

FIG. 19 illustrates an example method 101 for assessing electricalconnections based on rearrangement of an input data stream in ananalysis system, such as an assay cartridge qualification system. Atstep 110 of method 101, a circuit assembly of a first device (e.g.,assay cartridge) is loaded into a second device (e.g., instrument bay),such that the circuit assembly of the first device electricallyinterfaces with a circuit assembly of the second device. At step 120 ofthe method 101, an input data stream including impedance data blocks iscollected. The input data stream can include data elements, such ascharge data blocks, amplitude data blocks, impedance data blocks,current data blocks, volts data blocks, time data blocks, weight datablocks, brightness data blocks, distance data blocks or combinationsthereof. In some embodiments, the input data stream comprises a sequenceof bytes and/or pixels. In some embodiments, the input data stream maybe divided into a sequence of n data blocks, where each data blockrepresents a different electrode. For example, Block 1, Block 2, Block3, . . . , Block n corresponds to electrode 1, electrode 2, electrode 3,. . . , electrode n.

FIG. 27 shows a diagram of an example data block sequence of n datablocks formed into an array, labeled 300.

Referring back to FIG. 19, at step 130 of the method 101, eachidentified data block is reordered in accordance with the ROPE method.For example, in implementations of the step 130, the data blocks arereordered to match a reference order (RO), which can be based on apattern determined from analyzing a predetermined number of previouslyprocessed data blocks. The reordering of the data blocks based on the ROform a new data stream or new data block sequence. In some embodimentsof the method 101, the predetermined number of previously processed datablocks are identified before the start of the operation.

FIG. 28 shows a diagram of an example predetermined number of previouslyprocessed data blocks, formed as an array or matrix labeled 301. In theexample of FIG. 28, the previously processed data blocks (PP Block)include PP Blocks 1, 2, 3, . . . n. The values given represent thesecond location (new order) for the new data block.

For example, the new data blocks are formed by repositioning the inputdata blocks according to the reference order of the previously processeddata block. The above illustrated new data blocks can also be arrangedusing other relationships between the blocks. For example, any valuethat can be measured such as R², EFT, RFT, charge, current, volts,number of electrodes analyzed or combinations thereof.

Determining the Quality of the Fit

The amount any impedance value from an electrode (where the electrodesfrom the assay cartridge and assay device form a circuit) varies fromits expected value is determined by the quality of the fit (QOF). Thisdetermination might be different for different electrodes, and it mightbe normalized by the standard error of the fit.

Referring back to FIG. 19, in accordance with the ROPE method at step140 of the method 101, each re-ordered data block (new data blocksequence) is compared to how well the new data block fits a line per thequality of fit (QOF) parameters, such as R², EFT, RFT or combinationsthereof. For example, in some implementations, the re-ordered data blocksequence is compared to a line and if the new data blocks match or arewithin some tolerable threshold, they are considered a match. Forexample, in some implementations, the re-ordered data block sequence iscompared to the QOF parameters, as illustrated in sub-step 141, and ifthe data blocks match or are within some tolerable threshold, they areconsidered a match.

The method 101 includes a step 150 to determine whether the evaluatednew data block sequence meets a threshold with respect to the QOFparameters to pass, and subsequently implement step 160 to run theapplication of the analysis system, e.g., such as run the assay. Yet, ifthe evaluated block sequence does not meet the threshold with respect tothe QOF parameters and thereby fails, the method can implement a seriesof steps 170-220 to retest the first device (e.g., cartridge), or simplypermanently fail the test by implementing the process 230.

For example, some embodiments of the method 101 includes a step 170 toinitially eject the first device (e.g., assay cartridge); a step 180 toreload the first device into the second device (e.g., reload thecartridge in the bay (same bay or in a different bay) to interface thecircuit assembly of the cartridge with the electronics of the bay); astep 190, similar to step 120, to re-measure the impedance for eachelectrode; a step 200, similar to step 130, to reorder the impedancedata in accordance with the ROPE method; a step 210, similar to step140, to identify the pattern with the best fit including evaluating aquality of fit (at sub-step 211); and a step 220, similar to step 150,to determine whether the re-evaluated new data block sequence passes orfails; after which, the method 101 includes running the application atstep 240 if a pass, or ejecting the first device at step 230 if itfails.

FIG. 20 illustrates an example method 102 for assessing electricalconnections based on the rearrangement of an input data stream in ananalysis system, such as an assay cartridge qualification system. Themethod 102 includes the steps 110, 120 and 150 of the method 101. In themethod 102, at step 130B, each in accordance with the SOPE method. Forexample, in implementations of the step 130, the data blocks arereordered monotonically. As step 140B, each re-ordered data block (newdata block sequence) is compared to how well the new data block fits aline per the key parameters. The re-ordered data block is compared tothe key parameters and if the data blocks match or are within sometolerable threshold, they are considered a match. The example keyparameters may include the R², EFT, RFT or combinations thereof. Themethod 102 can also include the steps 170-220 of the method 101.

FIG. 21 illustrates an example method 103 for assessing electricalconnections based on rearrangement of an input data stream in ananalysis system, such as an assay cartridge qualification system. Themethod 103 includes the steps 110, 120 and 150 of the method 101. In themethod 103 at step 130C, each in accordance with the POPE method. Forexample, in implementations of the step 130C, each impedance value iscompared to a previously processed data block (e.g., the impedancevalues from a prior qualified run). In some implementations of the step130C, the data blocks may also be re-ordered monotonically. At step 140Cof the method 102, each re-ordered data block (new data block sequence)is compared to how well the new data block fits a line per thepredefined parameters. The re-ordered data block sequence is compared toa line and if the new data blocks match or are within some tolerablethreshold, they are considered a match. The re-ordered data blocksequence is compared to the predefined parameters and if the data blocksmatch or are within some tolerable threshold, they are considered amatch. In some embodiments of the method 103, the predefined parametersare the R², EFT, RFT or combinations thereof. The method 103 can alsoinclude the steps 170-220 of the method 101.

Other factors that can be evaluated in the QOF for the SOPE, POPE, andROPE methods are the intercept and/or slope. For example, in someimplementations, every time data is fitted to a line, two data pointsare generated the slope of the line and the intercept of the line.Intercept is also referred to as the offset. The intercept is the wherethe fitted line crosses the Y intercept. In some implementations, forexample, the intercept can be between 0-2000 units, e.g., preferablybetween 200-500 units. In some implementations, the slope of the fittedline can be between 1.5-10, e.g., preferably between 2-6. In someimplementations, if the slope of the line is less than 2 the cartridgeis failed.

Finding the Best Pattern: Run Matching Characteristics

In implementations of the ROPE method, once the patterns are determined,for example, the qualifier module 1806 analyses the patterns to find thebest pattern. The qualifier uses the quality of the fit (QOF) todetermine whether the connections are good.

In such implementations, the qualifier module 1806 may implement asearch operation for identifying an acceptable match. In someimplementations, a previously processed data block that fits the currentdata block acceptably is identified. In some implementations, the searchoperation can include seeking an acceptable match. In someimplementations, the previously processed data block that does not fitthe current data block acceptably is identified. In someimplementations, the search operation can include seeking anunacceptable match. In some implementations, the search operation caninclude seeking an acceptable and unacceptable match. In someimplementations, the previously processed data block that best matchesthe current data block is identified. In some implementations, thesearch operation can include seeking a best possible match as defined bythe QOF parameters.

In some implementations, the run match characteristics are thepredefined parameters. In some implementations, run matchingcharacteristics are the same and, in some implementations, they aredifferent. In some implementations, the number of run matchcharacteristics is always the same and, in some implementations, theyare different. For example, in some implementations, the run matchcharacteristic is the RFT or R². In some implementations, the run matchcharacteristic is the RFT and R². In some implementations, the first ROhas a first set of run matching characteristics (such as RFT and R²)while a second RO has a second set of run matching characteristics (suchas RFT or R²). Characteristics that can be matched include impedance,R², RFT, EFT, and combinations thereof.

In some implementations, each run match characteristic is given a runmatch number. In some implementations the run match number is the QOFnumber or the predefined parameter number. For example, a run that has amatch for R² will be given a first run match number and if the run alsohas a match for RFT it will be given a second run match number and thenthe first run match number and second run match number will be given atotal run match number. In some implementations, a “pass” signal isgenerated if the total run match number is greater than or equal to athreshold. In some implementations, a “fail” signal is generated if thetotal run match number is less than or equal to a threshold.

If the circuit assembly fails, for example, the steps 120-150 of themethod shown FIG. 19, 20 or 21 can be repeated for a next match location(e.g., such as with a different working device).

In other implementations, each run match number is analyzed to determine“pass” or “fail”, e.g., a total run match number is not generated. Forexample, in some implementations, a “pass” signal is generated if allthe run match numbers are greater than or equal to a threshold. In someimplementations, a “fail” signal is generated if all the run matchnumbers are less than or equal to a threshold. In some implementations,a “pass” signal is generated if one run match number is greater than orequal to a threshold. In some implementations, a “fail” signal isgenerated if one run match number is less than or equal to a threshold.

As alluded to above, identifying an acceptable match can take more thanone route. In some implementations, the connection assessment depends onhow well each electrode's impedance meets expectations—if any impedanceis too far from the fitted prediction, the preflight fails. Review ofinternal and external data provides the basis to define the ranges andthe limits, for example.

In some implementations, the run match characteristic is R². In someimplementations, the R² must be acceptable. In some implementations, anacceptable R² is between 0.5-0.99. In some implementations, the runmatch characteristic is the RFT. In some implementations, the RFT mustbe acceptable. In some implementations, an acceptable RFT is between20-30. In some implementations, the run match characteristic is R² andRFT. In some implementations, the R² and the RFT must be acceptable. Insome implementations, the R² must be the highest compared to other ROmodels and RFT must be the lowest compared to other RO models.

In some implementations, the run match characteristic is the EFT. Insome implementations, the EFT must be acceptable. In someimplementations, an acceptable EFT is between −5 and +5. In someimplementations, the run match characteristic is R², RFT and EFT. Insome implementations, the R², the RFT, and the EFT must be acceptable.In some implementations, the R² must be the highest compared to other ROmodels and RFT must be the lowest compared to other RO models and theEFT must be between −4 and +4.

Example: One Data Block Matches with Two or More Previously ProcessedData Blocks

In some implementations, for example, one data block may match with twoor more previously processed data blocks (RO). In these implementations,pass/fail can be determined based on either previously provided datablock. In some implementations, if both the R² and RFT have acceptablevalues, the cartridge passes the preflight test. In someimplementations, if one or the other of R² or RFT have acceptablevalues, the cartridge passes the preflight test. In someimplementations, if both R² or RFT have unacceptable values, thecartridge fails the preflight test. In some implementations, if one orthe other of R² or RFT have unacceptable values, the cartridge fails thepreflight test.

In an illustrative example, input data stream 1 has a current data block1 which matches with previously processed data block 1, 2, and 3.However, amongst the three previously processed data blocks, Block 1,Block 2, and Block 3, current data block 1 has the best match with,previously processed data block 3. Therefore, previously processed dataBlock 2 and Block 1 are discarded and the match relationship betweenpreviously processed data block 3 and current data block 1 is formed. Insome implementations, when a match relationship is formed the preflighttest passes. In some implementations, a match relationship must beformed and the EFT for each electrode must be between 3-5 to pass thepreflight test.

In an illustrative example, input data stream 1 has a current data block1 which has a run match characteristic with previously processed datablock 1, 2, and 3. Because, current data block 1 has a run matchcharacteristic with previously processed data block 1, 2, and 3 a matchrelationship between previously processed data blocks 1, 2 and 3 andcurrent data block 1 is formed.

In an illustrative example, input data stream 1 has a current data block1 which has a run match characteristic with previously processed datablock 1, 2, and 3. Because no previously processed data block 1, 2, or 3has a best match, no match relationship between previously processeddata blocks 1, 2 or 3 and current data block 1 is formed. When no matchrelationship is formed the preflight test fails. In someimplementations, the “best match” is the highest R² and lowest RFT. Insome implementations, the “best match” is the highest R², lowest RFT,and lowest EFT.

Evaluating Each Electrode

In some implementations, for example, once a match between a currentdata block and a previously processed data block has been found, thequalifier module 1806 analyses each electrode to determine its fit(e.g., EFT). The qualifier uses the EFT to determine whether eachelectrode is connected.

In these implementations, the qualifier may include an “examine”operation to scrutinize if each electrode is connected. In someimplementations, the examine operation can include seeking an acceptabletolerance. In some implementations, the examine operation can includeseeking an unacceptable tolerance. In some implementations, the examineoperation can include seeking an acceptable and unacceptable tolerance.

In some implementations, the examine characteristics include the QOFnumber or the predefined parameter number. In some implementations,examine characteristics are the same and, in some implementations, theyare different for each electrode. In some implementations, the number ofexamine characteristics is always the same and, in some implementations,they are different. For example, in some implementations, the examinecharacteristic is the EFT. In some implementations, the examinecharacteristic is the EFT and the impedance value. In someimplementations, the first RO has one set of matching examinecharacteristics (e.g., such as EFT and impedance value) while a secondRO has a different set of matching examine characteristics (e.g., suchas EFT or impedance value). Examine characteristics that can be matchedare the EFT, impedance value or amplitude or combinations thereof.

In some implementations, each examine matching characteristic is givenan electrode match number. For example, a run that has a match for EFTwill be given a first electrode match number and if the run also has amatch for the impedance value it will be given a second electrode matchnumber and then the first electrode match number and second electrodematch number will be given a total electrode match number. In someimplementations, a “pass” signal is generated if the total electrodematch number is greater than or equal to a threshold. In someimplementations, a “fail” signal is generated if the total electrodematch number is less than or equal to a threshold. For example, if thecircuit assembly fails in implementations of the method, the steps120-150 of the method shown FIG. 19, 20 or 21 can be repeated for a nextmatch location (a bay on a different assay device or a different bay onthe same assay device or even the same bay) if the total electrode matchnumber at a match location is less than the threshold, e.g., at steps180-220.

In other implementations, each electrode match number is analyzed todetermine “pass” or “fail”, e.g., a total electrode match number is notgenerated. For example, in some implementations, a “pass” signal isgenerated if all the electrode match numbers are greater than or equalto a threshold. In some implementations, a “pass” signal is generated ifone electrode match number is greater than or equal to a threshold. Insome implementations, a “fail” signal is generated if all the electrodematch numbers are less than or equal to a threshold. In someimplementations, a “fail” signal is generated if one electrode matchnumber is less than or equal to a threshold.

In some implementations, the examine matching characteristics is EFT. Insome implementations, the EFT must be acceptable. In someimplementations, an acceptable EFT is between 0 and less than 5. In someimplementations, an acceptable EFT is about 4 (open) or greater than −4(short).

Determine Quality of the Fit

In various implementations of the step 140, 140B or 14C of the method ofany of FIG. 19, 20 or 21, respectively, a quality of the fit (QOF)number is generated. In some implementations, each data point in the QOFnumber corresponds to one electrode location (EFT) and/or for all of theelectrode locations combined (RFT and/or R²). The QOF number can beevaluated for pass/fail. As one example, the input data stream caninclude 130 data blocks. A QOF number is generated after processing allof the 130 data blocks in the input data stream. For example, the QOFnumber can include a value for all of the data block values combined(RFT and R²) and for each data block (EFT).

In some implementations, the QOF number includes the QOF parameters orpredefined parameters. In some implementations, the QOF number includesthe run match characteristic and the examine matching characteristic. Insome implementations, the QOF number includes the run match number andthe electrode match number.

Referring to FIGS. 27-30, these diagrams illustrate examples of anaffinity matrix formed in accordance with the disclosed methods andsystems. For example, as shown in FIG. 27, the example affinity matrix300 can be formed after obtaining an impedance value for each electrode.In a second example, the affinity matrix 301, shown in FIG. 28, can beformed by assigning each current data block a new location aftercomparing it to a previously processed data block.

FIG. 29 shows a diagram of an example affinity matrix 302, which can beformed after comparing the current data block 1 to all 5 previouslyprocessed data blocks and generating pass/fail numbers (e.g., such asrun match number (RM#), electrode match number (EM#), QOF number (QOF#),or combinations thereof) associated with each previously processed datablock.

FIG. 30 shows a diagram of an example affinity array 303, whichdemonstrates an affinity number associated with each previouslyprocessed data block.

In these examples, the affinity number stands for a measure of thequality of the fit between data block x and previously provided datablocky. The higher the affinity number, the stronger the match betweenthe data blocks they represent. In addition, the affinity matrix can beformed based on a weight given to each match found. For example, aweight factor can be the number of electrodes above a predeterminedlimit for example 130.

In some implementations, the QOF factor for the SOPE method is based onR² and EFT (but in some instances, can include EFT). In someimplementations, the QOF factor for the ROPE method is based on R², RFTand EFT. In some implementations, the QOF factor for the POPE method isbased on R², RFT and EFT. Additionally, for all three methods, the QOFfactor can be based on the slope of the line and/or the intercept, forexample.

Determine if Additional Data Needs to be Analyzed.

FIG. 22 illustrates an alternate example of the method 101, 102 or 103that includes making a check to determine if additional data needs to beanalyzed. As shown in step 22141, the input data stream is checked tosee if there is another data block in the input data stream that needsto be compared. If there is no additional data block that needs to becompared, then the method goes to step 22144 and evaluates if theoriginal data block passes or fails. If it passes, then the circuitassembly is processed 22145 or if it fails the circuit assembly isejected 22146. If there is another data block in the input data streamthat needs to be compared, then the method goes to step 22142. At step22142, the new data block is received. At step 22143 the new data blockis analyzed. At step 22144, both the new and original data blocks areanalyzed for pass/fail. In some embodiments, if both data blocks pass,then the circuit assembly is processed 22145 or if both data blocks failthe circuit assembly is ejected 22146. In some embodiments, if one orthe other data blocks passes, then the circuit assembly is processed22145 or if one or the other data blocks fail the circuit assembly isejected 22146.

It is noted that, while the diagrams of FIG. 19-21 include steps 110-240that are arranged serially in the exemplary embodiments, otherembodiments of the subject matter may execute two or more steps that canbe implemented in parallel, e.g., using multiple processors or a singleprocessor organized as two or more virtual machines or sub-processors.Moreover, still other embodiments may implement the steps as two or morespecific interconnected hardware modules with related control and datasignals communicated between and through the modules, or as portions ofan application-specific integrated circuit. Thus, the example processflow diagrams are applicable to software, firmware, and/or hardwareimplementations.

Excluding Certain Impedance Values

Prior to rearranging or after rearranging impedance values, certain datablocks can be excluded from the pass/fail analysis. In someimplementations, for example, data blocks may be excluded for tworeasons (1) the electrode is highly variable run-to-run or, (2) theelectrode's impedance measurement is too high or too low.

Highly Variable Electrodes

In some embodiments, data blocks from known highly variable electrodesare excluded. In examples of different impedance values, a highlyvariable electrode is an electrode which, run-to-run, gives verydifferent impedance values. In some implementations, a highly variableelectrode varies by more than about 100 units between runs. In someimplementations, a highly variable electrode varies by about 100-2000units between runs. In this context, “unit” in relation to impedancevalues refers to the inverse of an ohm, e.g., 2 ohms=0.5 units.

In examples of variability of their scaled error across multiple runs,highly variable electrodes are identified by having unacceptablevariability of their scaled error across multiple runs, e.g., runsperformed on the same bay with different cartridges. To identify highvariability electrodes across multiple runs, the variability of theirscaled error across N runs is determined—electrodes with standarddeviation of the scaled error >1.5 may be excluded.

Adjusting the Fit of Certain Impedance Values

In some implementations, the index of each ordered electrode isadjusted, e.g., “stretched out” to improve the linearity of the fit. SeeFIG. 2A, see the spaces between x-values—indices—124 and 142).

Electrode's Impedance Measurement

In some implementations, certain electrodes can be excluded becausetheir impedance value is too high or too low or combinations thereof. Insome implementations, for example, an impedance value of above about2000 units is considered too high and is excluded. In someimplementations, for example, an impedance value of between 2000-25000units is considered too high and is excluded. In some implementations,for example, an impedance value of below 100 units is considered too lowand is excluded. In some implementations, for example, an impedancevalue of between 0-100 units is considered too low and is excluded. Inthis context, “unit” in relation to impedance values refers to theinverse of an ohm, e.g., 2 ohms=0.5 units.

In some implementations, electrodes with an impedance value that is toohigh or too low are identified by having unacceptable variability oftheir minimum scaled error or maximum scaled error or combinationsthereof.

Example Embodiments of an Assay System Including an Assay Cartridge andan Assay Processing Device

FIG. 31A shows a schematic illustration of an example embodiment of anassay processing device of an assay system, such as an automated,cartridge-multiplexing electrochemical detection system. The assayprocessing device 3140 includes a base station 3141 that includes acontrol console 3142, which in some embodiments includes a userinterface. The assay processing device 3140 includes an instrument bank3145 that includes one or more cartridge processing modules (“bays”)3146 operatively coupled to the base station 3141. In the example shown,the assay processing device 3140 can include a plurality of instrumentbanks 3145 operatively connected to the base station 3141. The one ormore cartridge bays 3146 of the instrument bank 3145 are configured toreceive an assay cartridge (not shown) and process the cartridge, e.g.,independently of other bays. In some embodiments, the instrument bank3145 is operatively coupled to the base station 3145 to exchange power,input and output data, and control signal transmissions, which can befrom processed user inputs entered on the control console 3142. Inimplementations of the assay processing system to perform an assay onthe assay cartridge loaded in a cartridge bay 3146, the system canconduct a preflight test of the electrical connections between theelectronics of the assay cartridge (e.g., PCB) and the electronics ofthe cartridge bay 3146 (e.g., “working device”) in accordance with thedisclosed methods, e.g., the method 1815 and method 1831.

PCB of an Example Assay Cartridge

An example of a printed circuit board (PCB) of an assay cartridge thatmay be used in example implementations of the disclosed systems andmethods for assessing electrical connections between the assay cartridgeand an assay processing device is described.

FIG. 23 shows a diagram of an example PCB 2300 of an assay cartridgedevice. The PCB 2300 includes a first surface and a second surface. Oneor more pre-defined areas defined on the first surface provide a PCBplane for the location of one or more electrical components thereon. Oneor more test pads provided on the second surface allow electricaltesting of the solder connection between the PCB 2300 and/or one or moreelectrical components of another electronic device, such as electricalcomponents in an assay cartridge bay. Two or more connectivity pointsare provided on the first surface in each of said pre-defined areas.

The diagram of FIG. 23 illustrates the electrowetting connections to acartridge, e.g., the numbered arrays along the top and bottom. Theelectrodes are numbered geometrically without regard to their expectedelectrical properties. The numbered boxes between the top and bottomarrays represent the electrowetting pads of the cartridge/consumable.The cartridge depicted in FIG. 23 has a bi-planer portion and aco-planer portion. Opens cannot be detected over the co-planer portionbut shorts can. The bi-planer portion can detect both opens and shorts.

The example PCB 2300 includes 158 PCB electrodes/pads 2301 that connectto a connector board of another electronic device, e.g., such as aconnector board shown in FIGS. 26A and 26B. Trace wires (not shown)connect the electrowetting pad electrodes 2302 to the PCBelectrodes/pads 2301. The PCB electrodes/pads 2301 interface with theconnector board assembly electrodes, e.g., depicted in FIGS. 26A and26B.

Connection Between Circuit Assembly of an Assay Cartridge and WorkingInstrument

To measure impedance in a preflight test of an assay cartridge in aprocessing bay, for example, the circuit assembly and working instrumentmust be connected. FIGS. 31B-31E show schematic illustrations depictingportions of an example electronic device for an assay cartridgeprocessing bay (“working device” or “working instrument”) and of acartridge PCB in electrical connection with the working instrument.

FIG. 31B shows an example connector board assembly 3100 of an assaycartridge bay, like 3146, shown without an interfacing PCB from an assaycartridge. The connector board assembly 3100 can include a supportstructure 3101 and support plate 3102, which can provide a structuralhousing for the electronic components of the connector board assembly3100. The connector board assembly 3100 can include a connector board3103, described in further detail below, which can be flexible. In someexample embodiments, such as for assays that include polymerase chainreaction (PCR), the connector board assembly 3100 can include PCRheaters 3104 and detection heaters 3105. In some example embodiments,the connector board assembly 3100 can include magnets 3106, e.g., forcapturing magnetic beads in the sample.

FIG. 31C shows the connector board assembly 3100 electrically interfacedwith a PCB 3150 of an assay cartridge, which is depicted in the diagramof FIG. 31C as transparent, i.e., the features of PCB 3150 outlined insolid lines over a transparent background so that the underlyingfeatures of the connector board assembly 3100 can be seen. The featuresof the example PCB 3150 are shown in the diagram of FIG. 23 for the PCB2300.

FIG. 31D shows a diagram illustrating the connector board assembly 3100with an assay cartridge 3160 which comprises the PCB 3150 (in a lowerregion of the assay cartridge 3160, not shown in FIG. 31D). In someembodiments, the connector board assembly 3100 can engage/disengage withthe assay cartridge 3160 by moving up and down via a screw (not shown).

FIG. 31E shows a perspective view of the example connector boardassembly 3100 electrically interfaced with the other components of theelectronic device (“working device”) of the cartridge bay 3146. Furtherdetails of the example cartridge bay 3146 and the assay cartridge aredescribed in U.S. Pat. No. 9,498,778, e.g., at FIGS. 36-43 of U.S. Pat.No. 9,498,778, which is incorporated by reference in its entirety forall purposes.

The connector board 3103 (also shown in FIG. 26B) can include pogo pins2603 (shown in FIGS. 26A and 26B), which connect the electrodes on theconnector board assembly to the cartridge PCB. The connector board 3103can include high-density connectors 2602 (shown in FIGS. 26A and 26B),which connect the electrodes on the connector board assembly to a PCB2605 on the bay, as shown in FIG. 31E. The pogo pins are connected tothe connector board assembly high-density connectors via trace wires(not shown). Pogo pins are spring loaded electrodes.

FIG. 26A shows a schematic diagram of an example embodiment of theconnector board 3103 of the example connector board assembly 3100. Inthis example, the connector board 3103 includes pogo pins 2603 that arespring loaded electrodes. In some embodiments, the electrodes on theconnector board assembly 3100 are not spring loaded. For example, thereis a 1:1 relationship between the pogo pins 2603 on the connector boardand the electrodes on the cartridge PCB. Also, for example, there is a1:1 relationship between the electrodes on the connector board's highdensity connector 2602 and the electrodes on the bay PCB (shown in FIG.31E). In this way, electricity can be provided from the bay PCB to theconnector board assembly high-density connectors 2602, and to theconnector board assembly pogo pins 2603 to the cartridge PCB. As shownin this example, the connector board 3103 includes magnets 3106 andheaters 3104 and 3105.

FIG. 26B shows an exploded view of the support plate 3102 and theconnector board 3103 of the example connector board assembly 3100. Shownare the connector board's high density connector 2602, pogo pins 2603,heaters 3104 and 3105 and magnets 3106.

Example Applications

The systems and methods in accordance with the disclosed technology canalso be used to ensure that each time a subsystem is added to a systemthe new subsystem is properly integrated. For example, in the ePlex®system produced by GenMark Diagnostics, Inc., each time a new bay isadded to an instrument (e.g., replacing a broken bay, non-performing bayor an updated bay), the bay is evaluated to ensure proper function. Partof the evaluation includes running test cartridges to ensure a properconnection is formed between the new bay and cartridges. Underconventional methods, a properly installed bay could be un-installed andre-installed because cartridges were failing the pre-flight test when infact they were properly connected, thus wasting time, effort and bays.In contrast, in example implementation of the disclosed methods, insteadof ejecting the cartridge, a “fail” signal (step 150 of the method 101illustrated in FIG. 19) is interpreted to mean the bay was improperlyinstalled. The fail signal at step 150 is particularly indicative of animproper bay installation if the bay had previously been used on anotherinstrument and functioned properly. The fail signal at step 150 isparticularly indicative of an improper bay installation if the bay typehad previously been used on another instrument and functioned properly.

Example Data and Results Example 1: Variability Based on StrictPreflight Impedance Testing

FIG. 24 shows a data plot depicting example average impedance values foreach electrode across multiple bays of different types of assaycartridge bays (e.g., TTM-2, TTM-3TTM-3b, and Lenthor) using theimpedance threshold method. Also plotted are the pass/fail limits forthe impedance measurements. As can be seen, every electrode has its ownlimits. As can be seen there is no relationship between the electrodes.As shown in the example data, the variability between the differentboard types is shown most clearly for electrode 137, but electrodes inthe 20-30 range, the 50-65 range, and the 90-100 range also showsubstantial differences between bay types. In FIG. 24, the Y-axis isconductance (inverse of ohm) and the X-axis is the electrode number(i.e. not re-ordered). This data demonstrates how difficult it is toassess the impedance data across multiple bays.

FIG. 25 shows a data plot depicting average impedance values associatedwith an example TTM3 bay. The example data in FIG. 25 illustrates thedifficulty in making an accurate pass/fail call on a sample with adefect. The squares on the chart show the average of the TTM-3 impedancereadings across many cartridges along with the electrode-by-electrodepass/fail limits. The circles show the impedance readings for eachelectrode of one cartridge run on one bay. For example, electrode 125 ofthis cartridge has a defect (short), and although the impedancemeasurement of this electrode appears higher than the averagemeasurement of this electrode, its value still passes. As a result, thesystem would run the assay and a potential false negative would resultpotentially impacting patient care.

The example data in FIGS. 24 and 25 illustrates that variability basedon strict preflight impedance testing can make it difficult to achieveaccuracy, e.g., it is subject to false failures or false passes. Forexample, if the limits are tight enough to minimize false passes, therate of false failures grows, but if the limits are loose enough toaccommodate bay-to-bay variability and minimize false failures, the rateof false passes grows. Moreover, because the upper and lower limitschange over the course of the year (data not shown), the limits need toeither be constantly re-evaluated or a wider limit set to avoid falsefailures (but this in turn obscures true failures).

Example 2: Determining the Expected Order Based on a TTM-2 Bay

The differences in manufactured cartridge bays that are different fromone another of their type may be caused by bay manufacturing variation,process variability, supplier changes, design changes, and othereffects. While these variabilities may be thought to be small and havelittle or no impact on validity, instead such variations can lead tochanges in assay validity because the differences impact pre-flightpass/fail determinations. As such impedance characteristics ofelectrodes from four different cartridge bay types from GenmarkDiagnostics, Inc. have been characterized, including the TTM-2, TTM-3,TTM-3b, and Lenthor type bays.

The TTM-2 bay was the first released variety of bays. In exampleimplementations using the TTM-2 bay, data was collected from over 6300preflight files from internal and external systems. The internal dataincludes test runs, quality control runs, and verification runs thatinclude open and short fault injects.

FIG. 1 shows a data plot depicting average impedance values obtainedfrom all electrodes on example PCBs of assay cartridges run in TTM-2bays and plotted monotonically. In FIG. 1, the Y-axis is conductance(inverse of ohm) and the X-axis is the ordered index (electrodes orderedmonotonically). The slope of the line is indicated as 5.1957 and theIntercept is 338.04. Here R² is 0.7775, applying the quality factor thiscartridge would be ejected because R² is not greater than 0.98.

FIG. 2A shows a data plot depicting average impedance values obtainedfrom all electrodes on example PCBs of assay cartridges run in TTM-2bays and plotted monotonically that fit a linear line, e.g., electrodesexcluded and stretched to fit a linear line. In this example, highvariability electrodes and all electrodes with impedance greater than2000 are excluded. The high variability electrodes were identified bythe variability of their scaled error across all 6300 runs. Electrodeswith standard deviation of the scaled error >1.5 were excluded. Afterselecting the electrodes, the index of each ordered electrode wasadjusted to improve the linearity of the fit (see the spaces betweenx-values—indices—124 and 142). The linear range was determinedsubjectively from FIG. 1. For example, in FIG. 2A, the Y-axis isconductance (inverse of ohm) and the X-axis is the ordered index(electrodes ordered monotonically). The slope of the line is indicatedas 4.0542 and the Intercept is 392.66. Here, in FIG. 2A, R² is 0.9968,applying the quality factors this cartridge would be processed becauseR² is greater than 0.98. For example, this demonstrates that excludinghigh variability electrodes, electrodes with impedance greater than 2000and adjusting the fit from the data shown in FIG. 1 changes the resultfrom ejecting the cartridge to processing the cartridge. FIG. 2A is anexample of the SOPE method.

FIGS. 2B-2D show data plots depicting impedance data from 3 differentcartridges run on TTM-2 bay types. FIG. 2B shows no defects, no failingelectrodes. FIG. 2C shows two failing electrodes (opens) at index 100and index 106. FIG. 2D shows two failing electrodes (shorts) at index 73and index 75. Shorts occur most often between neighboring electrodes,and these electrodes are neighbors. In FIGS. 2B-2D, the Y-axis isconductance (inverse of ohm) and the X-axis is the ordered index(electrodes ordered monotonically). The slope of the line is indicatedas Y and the Intercept is the number added to the slope value. R² isalso shown. FIGS. 2B-2D show data from example implementations of theSOPE method, where, the data from FIGS. 2B and 2C indicates that the PCBcartridge would be processed because R² is greater than 0.98; but thedata from FIG. 2D indicates that the PCB cartridge would be ejectedbecause R² is not greater than 0.98.

FIG. 3 shows a data plot depicting the standard error of the fit (RFT)for each run on the TTM-2 bays. For the TTM2 data set, the line steepensat about 28 and 28 is considered the subjective break line. Here, theworst point from each run is plotted. In this example, any electrodewith a standard error of the fit above 28 means the cartridge is notprocessed.

Next the data was assessed to determine if the cartridge contained anopen or short circuit. To do this, impedance values were re-rankedaccording to key parameters to look for a subjective break value.

FIG. 4 shows the data re-ranked according to the maximum scaled error(open) across the electrodes for each run. This data set looks forsensitivity to possible open circuits. Because the line steepens atabout 4 it is assumed that everything above 4 is a true open circuit.Thus, 4 is set as the subjective break value. Opens are shown at +4.0and above.

FIG. 5 shows the data re-ranked according to the minimum scaled error(shorts) across the electrodes for each run. This data set looks forsensitivity to possible short circuits. Because the line steepens atabout −4 it is assumed that everything below −4 is a true short circuit.Thus, −4 is set as the subjective break value. Shorts are shown at −4.0and below.

Once the expected order on the TTM-2 bay is determined, the order can beused in the ROPE method.

Example 3: Determining the Expected Order Based on a TTM3 Bay

The TTM3 bay was the second released variety of bays.

The TTM-3 bay was the second released variety of bays. In exampleimplementations using the TTM-3 bay, data was collected from over 170preflight files used for testing the TTM-3 design.

FIG. 6A shows a data plot depicting average impedance values obtainedfrom all electrodes on example PCBs of assay cartridges run in TTM3 baysand plotted monotonically (excluding high variability electrodes and allelectrodes with impedance greater than 2000). The high variabilityelectrodes were identified by the variability of their scaled erroracross all 170 runs. Electrodes with standard deviation of the scalederror >1.5 were excluded. For the TTM-3 data, the 5 electrodes measuringthe highest impedances fall above the best-fit line. Assigning thesepoints higher index values improves the fit of the line (the R2increases from 0.9915 to 0.992). In FIG. 6A, the Y-axis is conductance(inverse of ohm) and the X-axis is the ordered index (electrodes orderedmonotonically). The slope of the line is indicated as 3.7962 and theIntercept is 414.65. Here R² is 0.9915, applying the quality factorsthis cartridge would be processed because R² is greater than 0.98. Thisis an example of the SOPE method.

FIG. 6B shows a data plot depicting average impedance values forelectrodes on PCBs of assay cartridges run in TTM-3 bays and plottedmonotonically that fit a linear line. In FIG. 6B, the index of eachordered electrode was adjusted to improve the linearity of the fit (seethe spaces between x-values—indices—123). The linear range wasdetermined subjectively from the average impedance for all electrodesfrom PCBs run in TTM3 bays and plotted monotonically. In FIG. 6B, theY-axis is conductance (inverse of ohm) and the X-axis is the orderedindex (electrodes ordered monotonically). The slope of the line isindicated as 3.7773 and the Intercept is 415.45. Here R² is 0.992,applying the quality factors this cartridge would be processed becauseR² is greater than 0.98. This is an example of the SOPE method.

Once the order and functional form have been selected based onexpectations, then the impedance measurements of each electrode can beanalyzed. FIG. 6C shows a data set from a single cartridge with a defectat electrode 125. In the electrode reordering, electrode 125 falls atindex 103. This electrode is easily identifiable as defective by itsseparation from the least-mean squares linear fit. Its scaled error fromthe fit is 4.35, which is well above the 4.0 cutoff. Indeed, mostelectrodes' scaled errors do not exceed 3. In FIG. 6C, the Y-axis isconductance (inverse of ohm) and the X-axis is the ordered index(electrodes ordered monotonically). The slope of the line is indicatedas 3.4115 and the Intercept is 430.28. Here R² is 0.9833, applying thequality factors this cartridge would be ejected because R² is notgreater than 0.98. This is an example of the SOPE method.

FIG. 7 shows the standard error of the fit (RFT) for each run. For theTTM3 data set, the line steepens at about 28. In this example, anyelectrode with a standard error of the fit above 28 means the cartridgeis not processed. This data set highlights the need for standard errorof the fit (RFT) as a pass/fail factor. In runs with high RFT (above28—see the right-hand side of the plot), the opens' and shorts' extremesdid not exceed 4 in magnitude. As these errors are scaled by thestandard error of the fit, their absolute error was large.

FIG. 8 shows the data re-ranked according to the maximum scaled error(open) across the electrodes for each run. This data set looks forsensitivity to possible open circuits. Because the line steepens atabout 4 it is assumed that everything above 4 is a true open circuit.Thus, 4 is set as the subjective break value. Opens are shown at +4.0and above.

FIG. 9 shows the data re-ranked according to the minimum scaled error(short) across the electrodes for each run. This data set looks forsensitivity to possible short circuits. Because the line steepens atabout −4 it is assumed that everything below −4 is a true short circuit.Thus, −4 is set as the subjective break value. Shorts are shown at −4.0and below.

Once the expected order on the TTM3 bay is determined, for example, theorder can be used in the ROPE method.

Example 4: Determining the Expected Order Based on a TTM3-b Bay

The TTM3-b bay was the third released variety of bays. In exampleimplementations using the TTM-3 bay, data was collected from 68preflight files from test runs.

FIG. 10 shows the average impedance for all electrodes from PCBs run inTTM3-b bays and plotted monotonically (excluding high variabilityelectrodes and all electrodes with impedance greater than 2000). Thehigh variability electrodes were identified by the variability of theirscaled error across all 68 runs. Electrodes with standard deviation ofthe scaled error >1.5 were excluded. After selecting the electrodes, theindex of each ordered electrode was adjusted to improve the linearity ofthe fit (see the spaces between x-values—indices—123 and 140). Thelinear range was determined subjectively from the average impedance forall electrodes from PCBs run in TTM3-b bays and plotted monotonically.In FIG. 10, the Y-axis is conductance (inverse of ohm) and the X-axis isthe ordered index (electrodes ordered monotonically). The slope of theline is indicated as 3.9572 and the Intercept is 357.68. Here R² is0.9964, applying the quality factors this cartridge would be processedbecause R² is greater than 0.98. This is an example of the SOPE method.

FIG. 11 shows the standard error of the fit (RFT) for each run. For theTTM3-b data set, the line steepens at about 28. In this example, anyelectrode with a standard error of the fit above 28 means the cartridgeis not processed.

FIG. 12 shows the data re-ranked according to the maximum scaled error(open) across the electrodes for each run. This data set looks forsensitivity to possible open circuits. Because the line steepens atabout 4 it is assumed that everything above 4 is a true open circuit.Thus, 4 is set as the subjective break value. Opens are shown at +4.0and above.

FIG. 13 shows the data re-ranked according to the minimum scaled error(short) across the electrodes for each run. This data set looks forsensitivity to possible short circuits. Because the line steepens atabout −4 it is assumed that everything below −4 is a true short circuit.Thus, −4 is set as the subjective break value. Shorts are shown at −4.0and below.

Once the expected order on the TTM-3b bay is determined, the order canbe used in the ROPE method.

Example 5: Determining the Expected Order Based on Lenthor Bay

The Lenthor bay, e.g., an alternate of the TTM2 design) was the thirdreleased variety of bays. In example implementations using the TTM-3bay, data was collected from 403 preflight files from internal test runsand customer runs.

FIG. 14A shows the average impedance for all electrodes from PCBs run inLenthor bays and plotted monotonically (excluding high variabilityelectrodes and all electrodes with impedance greater than 2000). Thehigh variability electrodes were identified by the variability of theirscaled error across all 403 runs. Electrodes with standard deviation ofthe scaled error >1.5 were excluded. After selecting the electrodes, theindex of each ordered electrode was adjusted to improve the linearity ofthe fit (see the spaces between x-values—indices—138). The linear rangewas determined subjectively from the average impedance for allelectrodes from PCBs run in Lenthor bays and plotted monotonically. InFIG. 14A, the Y-axis is conductance (inverse of ohm) and the X-axis isthe ordered index (electrodes ordered monotonically). The slope of theline is indicated as 4.179 and the Intercept is 330.41. Here R² is0.9959, applying the quality factors this cartridge would be processedbecause R² is greater than 0.98. This is an example of the SOPE method.

FIG. 14B shows impedance data from a passing cartridge on a Lenthor typebay, plotted with the linear fit to the data. In FIG. 14B, the Y-axis isconductance (inverse of ohm) and the X-axis is the ordered index(electrodes ordered monotonically). The slope of the line is indicatedas 4.3559 and the Intercept is 347.53. Here R² is 0.9917, applying thequality factors this cartridge would be processed because R² is greaterthan 0.98. This is an example of the SOPE method.

FIG. 15 shows the standard error of the fit (RFT) for each run. For theLenthor data set, the line steepens at about 28. In this example, anyelectrode with a standard error of the fit above 28 means the cartridgeis not processed.

FIG. 16 shows the data re-ranked according to the maximum scaled error(open) across the electrodes for each run. This data set looks forsensitivity to possible open circuits. Because the line steepens atabout 4 it is assumed that everything above 4 is a true open circuit.Thus, 4 is set as the subjective break value. Opens are shown at +4.0and above.

FIG. 17 shows the data re-ranked according to the minimum scaled error(short) across the electrodes for each run. This data set looks forsensitivity to possible short circuits. Because the line steepens atabout −4 it is assumed that everything below −4 is a true short circuit.Thus, −4 is set as the subjective break value. Shorts are shown at −4.0and below.

Once the expected order on the Lenthor bay is determined, the order canbe used in the ROPE method.

Example 6: ROPE Method

In this example, impedance values (WIVs) were analyzed using the ROPEmethod. Table 1 lists the electrodes, impedance values, reordering byindex, and the resulting R², RFT, and EFT values. From the raw data thefollowing QOF factors were determined: Intercept=346.3522; EFT=3.573006;R²=0.969108; RFT=24.48453.

In this example, The RFT is below 28 and the EFT is below 4 but becauseR² is less than 0.98, the cartridge tested should be ejected andre-tested on another machine.

TABLE 1 Electrode Index (aka x) Impedance (aka y) EFT 11 1 339 0.44620815 2 344 0.387927 13 3 340 0.697225 9 4 366 −0.21874 17 5 351 0.53982 86 350 0.726591 6 7 363 0.341572 19 8 337 1.549397 10 9 377 0.061641 4 10370 0.493465 12 11 383 0.108447 21 12 367 0.90785 7 13 407 −0.57991 1414 408 −0.47482 128 15 411 −0.45142 16 16 424 −0.83643 117 17 442−1.42566 5 18 422 −0.46289 23 19 406 0.336511 2 20 424 −0.25272 140 21449 −1.12784 121 22 483 −2.37054 20 23 394 1.410333 132 24 450 −0.730918 25 404 1.29377 3 26 422 0.704541 120 27 439 0.156154 22 28 4240.914715 25 29 452 −0.08293 1 30 459 −0.2229 0 31 452 0.208923 29 32 467−0.25778 27 33 478 −0.56111 26 34 484 −0.66024 142 35 491 −0.8002 138 36509 −1.38943 33 37 498 −0.79424 52 38 486 −0.1582 28 39 508 −0.9108 3140 493 −0.15224 35 41 505 −0.49642 37 42 508 −0.47301 124 43 4701.224915 134 44 540 −1.4881 122 45 497 0.414036 129 46 503 0.314912 5447 506 0.338315 113 48 584 −2.70144 24 49 527 −0.22751 39 50 5160.367681 56 51 513 0.636137 60 52 514 0.741224 58 53 524 0.478732 66 54500 1.604872 68 55 509 1.383222 64 56 519 1.12073 93 57 507 1.756764 13058 573 −0.79289 30 59 553 0.169885 99 60 554 0.274972 41 61 561 0.135007131 62 585 −0.69927 36 63 552 0.794444 38 64 541 1.389636 101 65 5361.739776 97 66 570 0.497073 133 67 600 −0.58226 126 68 535 2.218406 13669 637 −1.80156 89 70 602 −0.22616 91 71 626 −1.06044 34 72 590 0.555806111 73 652 −1.83048 43 74 614 −0.13255 103 75 583 1.279488 32 76 645−1.10679 65 77 630 −0.34823 86 78 614 0.45117 95 79 638 −0.38311 40 80641 −0.35971 69 81 636 −0.00957 115 82 700 −2.47754 74 83 648 −0.2078271 84 659 −0.51115 76 85 625 1.023411 84 86 672 −0.75024 72 87 664−0.27757 55 88 635 1.052777 53 89 675 −0.43498 90 90 676 −0.32989 75 91681 −0.38817 92 92 646 1.18723 61 93 711 −1.32158 45 94 661 0.866457 7795 693 −0.29456 73 96 645 1.811789 94 97 693 −0.0027 96 98 722 −1.041288 99 679 0.860944 57 100 702 0.067505 70 101 667 1.642908 79 102 7030.318521 125 103 775 −2.47618 135 104 676 1.713116 67 105 712 0.38872942 106 713 0.493816 102 107 732 −0.13625 50 108 778 −1.86906 49 109 743−0.29366 59 110 748 −0.35194 107 111 821 −3.18749 154 112 739 0.307496151 113 767 −0.69015 153 114 752 0.068407 152 115 748 0.377704 156 116760 0.033528 87 117 708 2.303247 85 118 781 −0.5323 149 119 785 −0.54974147 120 802 −1.09812 144 121 780 −0.05367 150 122 755 1.113314 46 123778 0.319874 98 129 802 0.215238 155 130 821 −0.41483 148 131 7950.792991 100 132 807 0.448815 157 133 816 0.227165 51 134 823 0.08719978 142 843 0.43779

Example 7: Omitted Electrodes

Not all electrodes allow for detectable opens. For example, electrodesin the non-conductive top plate coating region do not allow fordetectable opens. Electrodes which have a lot of variability includeelectrode 115 (in a coplanar region of the PCB, in the amplificationzone), 158 (in a coplanar region of the PCB, in the detection zone), 88(in a biplanar region of the PCB, R4), 105 (in a biplanar region of thePCB, in the sample reservoir), 0 (in a coplanar region of the PCB, inthe amplification zone).

Each of the above described RO patterns includes at least 130electrodes. In these examples, preflight (and precheck) using thisversion of the impedance method may not be sensitive to opens or shortson these electrodes. In these examples, impedance measurements could notdetect opens from the non-conductive top plate region, but could detectshorts from these electrodes.

Table 2 lists electrodes excluded from these RO patterns.

TABLE 2 TTM- TTM- TTM- Top Plate 3b Lenthor 2 3 Region Location 44 44 4444 Conductive Det. Staging 47 47 Conductive Det. Staging 48 ConductiveDet. Staging 62 62 62 62 Test Capacitor Test Cap 63 63 63 63 TPReference Isolation 67 Conductive R1/R2 entry 78 Conductive R3 80Conductive R3 81 Conductive R3 82 82 82 82 Conductive R3 entry 83 83Conductive R3 104 104 104 104 Conductive R5 105 105 105 105 ConductiveR5 entry 107 Conductive PCR prep 109 109 109 109 Conductive PCR prep 115115 Non-Conductive PCR 119 119 119 119 Non-Conductive PCR 123 123 123123 Non-Conductive PCR 125 Non-Conductive PCR 127 127 127 127 TestCapacitor Test Cap 133 Non-Conductive PCR 135 135 Conductive PCR prep136 Non-Conductive PCR 137 137 Non-Conductive PCR 139 139 139 139Conductive PCR prep 141 141 141 141 Non-Conductive PCR 143 143 143 143Conductive R5 145 145 145 Conductive waste 146 Conductive R5 158 158 158Non-Conductive Detection 191 191 191 191 Test Capacitor Test Cap

Example 8: Reducing Validity Rates

The rate of incorrect results (false negatives or invalids) due to animproper connection between the assay cartridge and analysis deviceshould go down using the SOPE, ROPE or POPE methods compared to usingthe impedance threshold method. For example, it is expected that theerror rate could go from 0.2-0.3% using the impedance threshold methodto 0.05 to 0.035% using the ROPE, POPE or SOPE method.

Example 9: Detection of Fault Injects Using the ROPE Method

In this example, 12 bays (3 of each type of connector board0 TTMB-2,TTMB-3, TTMB-3b, and Lenthor) each ran the same 162 cartridges with twofault injects on each cartridge (either 2 opens in the co-planer region,2 opens in the bi-planer region or 1 tiebar and 1 HD connector short).Detection of the fault injects was assessed using the target impedance(plus threshold), i.e., the impedance threshold method and the ROPEmethod. For every type of failure, the ROPE method detected more faultsand had fewer false failures see Table 3 below. In particular, the ROPEmethod is significantly better at detecting tiebar shorts—these are hardshorts and are particularly useful to identify and fail the pre-flighttest if present.

Table 3 shows example values for detection of fault injects usingimpedance threshold method vs. the example ROPE method.

TABLE 3 Impedance Threshold ROPE Fault Method Method Detected non- 150244 tiebar shorts Missed non- 141  47 tiebar shorts Detected 187 266tiebar shorts Missed tiebar 112  33 shorts Detected  94 120 opens Missedopens 490 465 Detected fault 431 630 injects False Failures 177  71

Example 10: Target Detection Using ROPE

In this example, the ability for the assay system to detect expectedtargets after applying the ROPE pre-flight test was assessed. For 10cartridges tested, the following targets Bocavirus, Bordetellapertussis, Flu B, influenza A H3, NL63 (coronavirus), parainfluenzavirus 1, and respiratory syncytial virus (RSV) B were identified. Eachof the cartridges was valid and passed. There were no false negatives.Moreover, the signal of the detected target (Bordetella pertussis, NL63(coronavirus), human bocavirus, influenza A H3, influenza B,parainfluenza virus 1, and RSVB) using the ROPE method was comparable tothe signal obtained using the impedance target method.

Example 11: POPE Method

In this example, two pre-flight tests run on TTM2 bays were assessed. Inthis example, the example implementation of the POPE method had thefollowing methodology (e.g., example data in Table 4 below): find theright pattern for the impedance measurements (in this case, TTM2); findthe EFT of each index for both runs (scaled error for each index);because the previous preflight was valid, use it for POPE; subtract theprevious preflight's EFTs from the current preflight's EFTs; andidentify any indices that fail the threshold (e.g., beyond 3 sigma)—nonefailed in this case.

Alternatively, as discussed above, rather than comparing the EFT fromthe prior valid run and the preflight run, the impedance values from theprior valid run and impedance values from the preflight run could becompared. Again, after subtracting the impedance value from the priorvalid run from the impedance value from the preflight run any indicesthat fail the threshold (e.g., beyond 4 sigma) the cartridge is ejected.

TABLE 4 POPE method: (Prior valid Prior valid Pre-flight EFT minusimpedance impedance Prior valid Preflight preflight TTM- values valuesEFT EFT EFT) 2 VLP0731- VLP0731- VLP0731- VLP0731- VLP0731- Electrodeindex 390_ISW_1 608_ISW_1 390_ISW_1 608_ISW_1 608_ISW_1 25 1 430 4271.537435 1.442415 −0.09502 23 2 416 430 1.810745 0.916487 −0.89426 27 3437 428 0.419596 0.745977 0.326381 29 4 463 457 1.138185 1.037379−0.10081 14 5 457 450 1.012789 0.791576 −0.22121 13 6 452 452 0.868740.974187 0.105447 16 7 453 445 0.96417 0.611116 −0.35305 20 8 441 4380.351684 0.198409 −0.15328 22 9 443 444 0.393192 0.449584 0.056391 15 10454 450 0.843415 0.66172 −0.1817 12 11 455 453 0.753715 0.676184−0.07753 19 12 448 444 0.229511 0.00722 −0.22229 21 13 440 437 0.3730850.578579 0.205494 18 14 452 452 0.004647 0.011856 0.007208 17 15 465 4600.412628 0.202543 −0.21009 11 16 464 463 0.101298 0.105608 0.00431 10 17464 463 0.172861 0.167096 −0.00576 9 18 470 468 0.155777 0.1771910.021414 26 19 465 465 0.698317 0.630298 −0.06802 28 20 484 481 0.0406110.053701 0.01309 8 21 474 482 0.841662 0.297231 −0.54443 7 22 486 4810.538711 0.651112 0.112401 6 23 504 502 0.066598 0.193343 0.126745 5 24507 505 0.078656 0.05891 −0.01975 24 25 507 501 0.370612 0.454130.083518 121 26 520 518 0.004758 0.180223 0.175465 117 27 518 5170.386071 0.161293 −0.22478 31 28 546 539 0.745748 0.755052 0.009304 12829 520 521 0.826454 0.501435 −0.32502 30 30 545 535 0.170012 0.008899−0.16111 132 31 538 536 0.432084 0.217926 −0.21416 4 32 542 538 0.4734330.365818 −0.10761 3 33 542 538 0.70712 0.615875 −0.09124 33 34 568 5590.373186 0.284583 −0.0886 140 35 571 562 0.307002 0.211365 −0.09564 12036 566 556 0.152704 0.345513 0.192809 1 37 577 568 0.198863 0.084256−0.11461 32 38 588 577 0.557959 0.356627 −0.20133 130 39 575 5750.280913 0.035539 −0.24537 142 40 579 576 0.259556 0.116903 −0.14265 13841 587 577 0.031243 0.264526 0.233283 134 42 590 585 0.048445 0.026552−0.02189 35 43 601 594 0.34099 0.269736 −0.07125 34 44 601 596 0.1824170.188105 0.005688 2 45 595 594 0.273753 0.108591 −0.16516 122 46 591 5870.626486 0.675361 −0.11461 124 47 597 594 0.474759 0.477936 −0.20133 3748 602 603 0.371568 0.170442 −0.24537 36 49 610 607 0.116734 0.134677−0.14265 93 50 595 600 1.016418 0.697966 0.233283 38 51 630 617 0.594180.045413 −0.02189 52 52 638 631 0.84814 0.624415 −0.07125 0 53 642 6390.899722 0.875157 0.005688 89 54 603 614 1.209906 0.673362 −0.16516 3955 636 629 0.293038 0.045685 0.048874 113 56 628 636 0.265872 0.1434930.003178 54 57 638 630 0.075366 0.378524 −0.20113 41 58 640 622 0.0108111.012967 0.017943 99 59 630 639 0.660785 0.2896 −0.31845 97 60 645 6620.081947 0.756492 −0.54877 126 61 669 659 0.943631 0.382233 −0.22373 9162 642 659 0.597008 0.166911 −0.02457 101 63 655 668 0.134818 0.437178−0.53654 129 64 684 683 1.124962 1.029553 −0.24735 74 65 683 687 0.872491.018101 −0.12238 56 66 672 652 0.111943 1.122174 0.303158 72 67 711 7051.856016 1.525745 1.002156 57 68 701 704 1.133811 1.228023 −0.37119 5569 693 698 0.506222 0.653553 0.674545 43 70 704 685 0.827005 0.306404−0.5614 40 71 714 710 1.092135 0.799276 −0.4301 95 72 709 707 0.5989080.376228 0.30236 75 73 686 699 0.803001 0.322554 −0.09541 92 74 708 7140.050096 0.228292 0.145611 77 75 711 718 0.054941 0.177375 1.01023 13676 731 721 0.689952 0.069774 −0.33027 71 77 737 740 0.728705 0.831850.094212 86 78 747 751 0.965654 1.15696 0.147331 58 79 724 716 0.4564661.024011 −0.5206 111 80 741 758 0.128388 0.988602 −0.29286 94 81 735 7330.442488 0.647484 −0.22268 103 82 744 758 0.260402 0.440651 −0.48045 7383 740 746 0.730605 0.484778 0.178196 76 84 750 748 0.496694 0.6454680.122434 90 85 744 752 1.064314 0.694363 −0.62018 53 86 754 755 0.8259820.794226 0.103145 70 87 803 797 1.37388 1.234141 0.191306 79 88 752 7581.443428 1.144358 0.567544 69 89 746 739 1.996525 2.428223 0.860214 4590 764 751 1.339165 2.017763 0.204996 88 91 773 778 1.127667 0.7838450.180249 59 92 838 841 1.902362 2.417812 −0.24583 115 93 804 7980.031272 0.146231 0.148774 96 94 751 760 2.911078 2.42999 −0.36995 68 95809 796 0.209036 0.675031 −0.03176 131 96 806 813 0.561084 0.053804−0.13974 125 97 772 772 2.460481 2.36732 −0.29907 60 98 781 768 2.191252.764096 0.431699 50 99 830 816 0.096212 0.31944 0.678598 84 100 849 8470.887242 1.208637 −0.34382 98 101 808 808 1.32446 1.06654 0.51545 87 102883 888 2.298287 3.148603 0.11496 100 103 863 877 1.160658 2.416274−0.48109 42 104 847 833 0.233295 0.105016 0.465995 85 105 858 8620.670619 1.357399 −0.50728 107 106 853 852 0.31294 0.702823 0.389883 151107 855 838 0.314369 0.163341 0.572845 66 108 880 866 1.47737 1.2632520.223228 149 109 853 832 0.034967 0.682871 0.321395 153 110 860 8430.304058 0.175401 −0.25792 154 111 865 845 0.47552 0.156978 0.850316 61112 862 866 0.246364 0.895624 1.255616 155 113 870 836 0.568656 0.832089−0.12828 152 114 873 856 0.636817 0.158553 0.686779 150 115 869 8600.347973 0.27044 0.389883 49 116 851 846 0.652076 0.608076 −0.15103 147117 876 865 0.495729 0.297695 −0.21412 156 118 893 883 1.2273 1.1327010.647904 64 119 861 850 0.519649 0.829833 −0.12866 144 120 863 8670.581486 0.092881 −0.31854 148 121 883 877 0.23413 0.234909 0.64926 65122 883 885 0.014531 0.421338 0.263433 157 123 896 881 0.411704 0.083103−0.47826 102 124 921 917 1.370057 1.548503 −0.07753 51 125 918 9100.875342 0.790017 −0.044 46 126 924 906 0.779191 0.1408 −0.19803 81 127920 921 0.12095 0.465884 −0.0946 78 128 948 952 1.002425 1.5950540.310185 67 129 884 880 2.810172 2.960198 −0.48861 133 130 947 9500.328533 0.136171 0.000779 48 131 1003 988 1.710454 1.399198 0.406807146 132 989 982 0.134405 0.166648 −0.3286 80 133 1004 1004 0.0953210.350788 0.178447 47 134 1017 1002 0.54543 0.890206 −0.08533 158 1351048 1032 0.22241 0.516548 −0.63839 83 136 1042 1057 1.899209 0.5541850.344934 145 137 1108 1082 0.114688 0.742133 0.592629 82 138 1087 10922.865046 1.90928 0.150026 109 139 1144 1144 1.878576 0.963691 −0.19236104 140 1206 1174 0.834601 1.404234 −0.31126 44 141 1269 1205 0.0514641.992027 0.032243 135 142 1301 1301 0.842431 0.744188 0.255467 143 1431442 1382 3.497324 2.432131 0.344775 105 144 1467 1428 1.756354 1.966680.294138

Example 12: Pogo Pin Connection Test

In this example, a different method was used to identify short or opencircuits. Here, an open circuit impedance measurement is taken bymeasuring the impedance between two pins (one on the PCB and one on theworking device) and a short circuit impedance measurement is taken bymeasuring the impedance at a single pin. The open and short circuitmeasurements are compared to each other. If the difference between theopen and short circuit measurements is above a threshold, there is atrue open circuit and the cartridge should be ejected and discarded. Ifthe difference between the open and short circuit measurements is belowa threshold, there is not a true open circuit (false open circuit error)and the cartridge should be ejected and re-tested in another bay. Insome embodiments, the threshold is about 4000 units. In someembodiments, the threshold is between about 2000-6000 units.

Example 13: High Frequency Impedance for Detection of Shorts inPreflight Test

In this example, a different method was used to identify short circuits.Impedance is a function of frequency. As discussed above, generally,impedance is equal to resistance plus capacitance plus inductance.Capacitance plays a large role in impedance testing. Indeed, it isbelieved that the large difference between impedance values amongstelectrodes is dependent on capacitance. Capacitance is cause by padsize, top plate coating, trace location etc. It was observed that if thefrequency goes up (increased about 100 fold, e.g., from about 10 kHz to100 kHz) capacitance goes to zero. Stated another way, as frequency goesto infinity, capacitance offers no electrical impedance. This approachcannot, however, identify shorts. A pogo pin missing a pad by a smalldistance or a contaminant gives the same impedance value as a circuitwith a bad capacitor which the high frequency will ignore. Nevertheless,this approach is quick, e.g., about 10× faster due to 10× higherfrequency.

FIG. 32 shows a data plot depicting example impedance measurements at 10kHz and 100 kHz. As can be seen, variability electrode to electrode isreduced and shorts at electrodes 24/26, 68/70, 144/146 can be easilyvisualized. The opens on electrodes 1, 9, 37, 47, and 156 cannot beseen. The hits above 15000 units for the default 10 kHz assay are testcapacitors and not shorts.

Table 5 below shows the example conditions for the testing.

TABLE 5 High Frequency Impedance Settings For Detection Of Shorts InPreflight Test parameter min max default “Shorts Test” Voltage 60   300300 100 Mode DC/(−)DC AC DC AC AC Freq 10  1000 0 10 Start freq 1  99k10,000 99,000 Sweep pts 1  512 8 8 amplitude 200 mV 2 V 2 2 Freq step 1524k 0 0 cycles 1 2044 15 15 PGA gain 1   5 1 1

Examples

Various example embodiments in accordance the disclosed technology aredescribed.

Example A1 includes a method for confirming a PCB is connected to aworking device, the method comprising: obtaining the impedance value foreach electrode on the PCB; re-ordering the impedance values; comparingthe quality of the fit of the re-ordered impedance values to a straightline; determining if the PCB is connected to the working device.

Example A2: The method of Example A1, wherein the impedance values arere-ordered to match a reference order, or are reordered from lowest tohighest.

Example A3: The method of Example A1, wherein the QOF comprisesdetermining the maximum scaled error or minimum scaled error orcombinations thereof.

Example A4: The method of Example A3, wherein a minimum scaled errorvalue of about 20-40 indicates an open or short circuit on the PCB.

Example A5: The method of Example A3, wherein a maximum scaled error ofabout 3-10 indicates an open circuit on the PCB.

Example A6: The method of Example A3, wherein a minimum scaled error ofabout −3 to −15 indicates a short circuit on the PCB.

Example A7: The method of Example A1, wherein electrodes with highvariability are excluded from the evaluation.

Example A8: The method of Example A1, wherein the index of theelectrodes are adjusted to improve the quality of the fit.

Example A9: The method of Example A1, wherein electrodes with standarddeviation of the scaled error >1.5 are excluded from the evaluation.

Example B1 includes a method for identifying a short or open circuit ona PCB after the PCB is loaded into a working device, the methodcomprising: obtaining the impedance value for each electrode on the PCB;re-ordering the impedance values; evaluating the quality of the fit ofthe re-ordered impedance values; determining if the PCB has an short oropen circuit.

Example B2: The method of Example B1, wherein the impedance values arere-ordered to match a reference order, or are reordered from lowest tohighest.

Example B3: The method of Example B1, wherein the QOF comprisesdetermining the maximum scaled error or minimum scaled error orcombinations thereof.

Example B4: The method of Example B3, wherein a minimum scaled errorvalue of about 20-40 indicates an open or short circuit on the PCB.

Example B5: The method of Example B3, wherein a maximum scaled error ofabout 3-10 indicates an open circuit on the PCB.

Example B6: The method of Example B3, wherein a minimum scaled error ofabout −3 to −15 indicates a short circuit on the PCB.

Example B7: The method of Example B1, wherein electrodes with highvariability are excluded from the evaluation.

Example B8: The method of Example B1, wherein the index of theelectrodes is adjusted to improve the quality of the fit.

Example B9: The method of Example B1, wherein electrodes with standarddeviation of the scaled error >1.5 are excluded from the evaluation.

Example C1 includes a system for identifying a short or open circuit ona PCB after the PCB is loaded into a working device, the working devicecomprising: a measurer for measuring impedance values; a processor forre-ordering the electrodes and evaluating the quality of the fit of there-ordered impedance values.

Example C2: The system of Example C1, wherein measurer is coupled t theprocessor.

Example C3: The system of Example C1, wherein the processor comprises apattern module and a pass/fail module.

Example C4: The system of Example C1, wherein the processor is remotelyconnected to the working device.

Example C5: The system of Example C1, wherein the working devicecomprises a PCB interface.

Example D1 includes a working device comprising a PCB interface,impedance measuring module, an analysis module and a control module.

Example D2: The working device of Example D1 wherein the analysis modulecomprises a pattern module and a pass/fail module.

In some example embodiments in accordance with the disclosed technology(example E1), a method includes receiving an input data streamcomprising at least one data block; rearranging the sequence of datablocks in the input data stream to match one or more previouslyprocessed data blocks thereby forming a new data stream comprising atleast one new data block; determining the quality of the fit (QOF)between the new data stream to a straight line; and sending a signalpassing the input data stream or failing the data stream.

Example E2 includes the method of example E1, further comprising:identifying a first position for each data block in the input datastream and identifying a second position for each new data block fromthe new data stream.

Example E3 includes the method of example E1, further comprising priorto step b: identifying each data block to be excluded from the inputdata stream.

Example E4 includes the method of example E1, further comprising afterstep b: identifying each data block to be excluded from the input datastream.

Example E5 includes the method of example E1, further comprising priorto step d: determining if there is a next data block in the input datastream that should be analyzed and if so, repeating the re-ordering anddetermining steps for the next data block.

Example E6 includes the method of example E1, further comprising afterto step d: forming the affinity array.

Example E7 includes the method of example E6, wherein forming theaffinity array comprises determining run match number, an electrodematch number and a QOF number.

In some example embodiments in accordance with the disclosed technology(example E8), a computer readable medium having instructions which whenexecuted by a computing platform result in execution of a methodcomprising: receiving an input data stream comprising data blocks;rearranging the sequence of data blocks in the input data stream tomatch one or more previously processed data blocks thereby forming a newdata stream comprising at least one new data block; determining thequality of fit (QOF) between the new data stream to a straight line;sending a signal passing the input data stream or failing the input datastream.

Example E9 includes the computer readable medium of example E8, furthercomprising: identifying a first position for each data block in theinput data stream and identifying a second position for each new datablock from the new data stream.

Example E10 includes the computer readable medium of example E8, furthercomprising prior to step b: identifying each data block to be excludedfrom the input data stream.

Example E11 includes the computer readable medium of example E8, furthercomprising after step b: identifying each data block to be excluded fromthe input data stream.

Example E12 includes the computer readable medium of example E8, furthercomprising prior to step d: determining if there is a next data block inthe input data stream that should be analyzed and if so, repeating there-ordering and determining steps for the next data block.

Example E13 includes the computer readable medium of example E8, furthercomprising after to step d: forming the affinity array.

Example E14 includes the computer readable medium of example E13,wherein forming the affinity array comprises determining run matchnumber, an electrode match number and a QOF number.

In some example embodiments in accordance with the disclosed technology(example E15), an apparatus comprising: an input module that receives aninput data stream comprising at least one data block; a comparator thatcompares each data block with each of a predetermined number ofpreviously processed data blocks; and a qualifier that determines thequality of the fit (QOF) between the new data stream to a straight linewherein the qualifier forms an affinity array, wherein each element inthe affinity array comprises an affinity number based on the run matchnumber, an electrode match number, a QOF number or combinations thereof.

Example E16 includes the apparatus of example E15, further comprising acontroller.

Example E17 includes the apparatus of example E15, wherein the inputmodule is connected to the comparator.

Example E18 includes the apparatus of example E15, wherein thecomparator and qualifier are remotely associated with the apparatus.

In some example embodiments in accordance with the disclosed technology(example F1), an automated electrochemical detection system for assayinga patient sample includes an assay cartridge including a printed circuitboard (PCB) having a plurality of electrical interface connectionscorresponding to a plurality of electrodes in the PCB operable toimplement an assay in the assay cartridge; and an assay processingdevice including (i) an instrument bank including a cartridge bay havingan electronic unit that interface with the assay cartridge when insertedin the cartridge bay to implement the assay, wherein the electronic unitincludes a plurality of electrical conductor sites to contact at leastsome of the plurality of electrical interface connections of the assaycartridge PCB, and (ii) a base station including a data processing unitto control functionality of the assay processing device and/or processthe acquired data to produce an output for the electrochemicaldetection-based assay, wherein the assay processing device is configuredto conduct a preflight test assessing electrical connection integrity ofthe PCB of the assay cartridge with the electronic unit of the cartridgebay prior to implementing the assay, wherein, in conducting thepreflight test, the assay processing device measures an electricalsignal to determine an impedance value associated with at least some ofthe electrodes of the assay cartridge PCB; analyzes the determinedimpedance value to evaluate a quality factor (also referred to as a QOFfactor) of the electrical connection between the assay cartridge PCB andthe electronic unit of the assay processing device; and determines acommand for initiating an assay procedure when the quality factor is ator above a predetermined standard, or determines a command for ejectingthe assay cartridge from the assay processing device when the qualityfactor is below the predetermined standard.

Example F2 includes the system of example F1, wherein the assayprocessing device analyzes the determined impedance value by assigningthe determined impedance values into data blocks, wherein the each datablock corresponds to each electrode associated with the impedance value;organizing the data blocks into a sequence; and determining the qualityfactor of the electrical connection by calculating two or moreparameters associated with the sequence of the data blocks andevaluating the two or more parameters each to a predetermined thresholdvalue or threshold range.

Example F3 includes the system of example F2, wherein the assayprocessing device organizes the data blocks by reordering the datablocks into a monotonical sequence.

Example F4 includes the system of example F3, wherein the monotonicalsequence includes a lowest-to-highest monotonical sequence where anearlier data block in the sequence having a first impedance valueprecedes a latter data block in the sequence having a second impedancevalue that is greater than the first impedance value, or wherein themonotonical sequence includes a highest-to-lowest monotonical sequencewhere an earlier data block in the sequence having a first impedancevalue precedes a latter data block in the sequence having a secondimpedance value that is less than the first impedance value.

Example F5 includes the system of example F2, wherein the assayprocessing device organizes the data blocks by reordering the datablocks based on a predetermined reference order (RO) to create amonotonic sequence of the reordered data blocks.

Example F6 includes the system of example F2, wherein the assayprocessing device, prior to organizing the data blocks, compares theimpedance values to prior impedance values obtained from one or moreprevious preflight tests using the cartridge bay of the assay processingdevice, and wherein the assay processing device organizes the datablocks by reordering the data blocks based on a prior reference order(PRO) at least partially determined by an average of prior valid runs ofprior assay cartridges.

Example F7 includes the system of example F2, wherein the two or moreparameters are selected from a group consisting of a correlationcoefficient (R²), a scaled error of fit for an electrode fit test (EFT),a standard error of fit for a run fit test (RFT), and a tolerancedifference value includes a difference of an R² associated with adifferent assay cartridge and the R² associated with the assaycartridge, or a difference of an RFT associated with a different assaycartridge and the RFT associated with the assay cartridge.

Example F8 includes the system of example F1, wherein the assaycartridge includes reagents to assay a panel of respiratory pathogens,central nervous system pathogens, gastrointestinal pathogens, fungalpathogens, HCV pathogens, gram positive bacteria, or gram negativebacteria from a patient sample.

In some example embodiments in accordance with the disclosed technology(example F9), a method for preflight test assessing electricalconnection integrity of an assay cartridge interfaced with an assayprocessing device includes establishing an electrical connection between(i) an assay cartridge including a printed circuit board (PCB) having aplurality of electrical interface connections corresponding to aplurality of electrodes in the PCB and (ii) an electronic unit in acartridge bay of an assay processing device, wherein the electronic unitincludes a plurality of electrical conductor sites to contact at leastsome of the plurality of electrical interface connections of the assaycartridge PCB; measuring an electrical signal to determine an impedancevalue associated with at least some of the electrodes of the assaycartridge PCB; analyzing the determined impedance value to evaluate aquality factor of the electrical connection between the assay cartridgePCB and the electronic unit of the assay processing device; anddetermining a command for initiating an assay procedure when the qualityfactor is at or above a predetermined standard, or determining a commandfor ejecting the assay cartridge from the assay processing device whenthe quality factor is below the predetermined standard.

Example F10 includes the method of example F9, wherein the analyzingincludes assigning the determined impedance values into data blocks,wherein the each data block corresponds to each electrode associatedwith the impedance value; organizing the data blocks into a sequence;and determining the quality factor of the electrical connection bycalculating two or more parameters associated with the sequence of thedata blocks and evaluating the two or more parameters each to apredetermined threshold value or threshold range.

Example F11 includes the method of example F10, wherein the organizingthe data blocks includes reordering the data blocks into alowest-to-highest monotonical sequence where an earlier data block inthe sequence having a first impedance value precedes a latter data blockin the sequence having a second impedance value that is greater than thefirst impedance value, or wherein the organizing the data blocksincludes reordering the data blocks into a highest-to-lowest monotonicalsequence where an earlier data block in the sequence having a firstimpedance value precedes a latter data block in the sequence having asecond impedance value that is less than the first impedance value.

Example F12 includes the method of example F11, further comprising,prior to or after the organizing the data blocks into the monotonicalsequence, excluding one or more data blocks can be excluded based on acomparison of the impedance value with a previous impedance valueassociated with a prior preflight test.

Example F13 includes the method of example F10, wherein the organizingthe data blocks includes reordering the data blocks based on apredetermined reference order (RO) to create a monotonic sequence of thereordered data blocks.

Example F14 includes the method of example F13, wherein thepredetermined reference order is produced from an analysis of internaland external data that define a pattern of impedance values associatedwith the corresponding electrodes.

Example F15 includes the method of example F14, further comprisinggenerating the predetermined reference order based on a frequencypattern identified from three or more preflight tests, wherein thefrequency pattern is produced by averaging impedance values associatedwith the corresponding electrode for each of the three or more preflighttests and ordering them monotonically.

Example F16 includes the method of example F15, wherein the monotonicsequence of reordered data blocks includes a lowest-to-highestmonotonical sequence where an earlier data block in the sequence havinga first impedance value precedes a latter data block in the sequencehaving a second impedance value that is greater than the first impedancevalue, or wherein the monotonic sequence of reordered data blocksincludes a highest-to-lowest monotonical sequence where an earlier datablock in the sequence having a first impedance value precedes a latterdata block in the sequence having a second impedance value that is lessthan the first impedance value.

Example F17 includes the method of example F16, further comprising,prior to or after the reordering the data blocks based on apredetermined reference order, excluding one or more data blocks can beexcluded based on a comparison of the impedance value with a previousimpedance value associated with a prior preflight test.

Example F18 includes the method of example F10, further comprising,prior to the organizing the data blocks, comparing the impedance valuesto prior impedance values obtained from one or more previous preflighttests using the cartridge bay of the assay processing device, whereinthe organizing the data blocks includes reordering the data blocks basedon a prior reference order (PRO) at least partially determined by anaverage of prior valid runs of prior assay cartridges.

Example F19 includes the method of example F18, further comprising,prior to or after the reordering the data blocks based on apredetermined reference order, excluding one or more data blocks can beexcluded based on a comparison of the impedance value with a previousimpedance value associated with a prior preflight test.

Example F20 includes the method of any of the examples F10-F19, whereinthe two or more parameters any of: a correlation coefficient (R²), ascaled error of fit for an electrode fit test (EFT), a standard error offit for a run fit test (RFT), and a tolerance difference value includesa difference of an R² associated with a different assay cartridge andthe R² associated with the assay cartridge, or a difference of an RFTassociated with a different assay cartridge and the RFT associated withthe assay cartridge.

Example F21 includes the method of example F20, wherein a firstparameter includes the correlation coefficient, and a second parameterincludes the scaled error of fit for EFT.

Example F22 includes the method of example F20, wherein a firstparameter includes the correlation coefficient, and a second parameterincludes the standard error of fit for RFT.

Example F23 includes the method of example F20, wherein a thirdparameter includes the scaled error of fit for EFT.

Example F24 includes the method of example F20, wherein a firstparameter includes the correlation coefficient, a second parameterincludes the standard error of fit for RFT, and a third parameterincludes the tolerance difference value.

Example F25 includes the method of example F20, wherein each data blockincludes one or more data including the impedance value determined forthe corresponding electrode, and an index number associated only withthe data block.

Example F26 includes the method of example F9, wherein the assaycartridge includes reagents to assay a panel of respiratory pathogens,central nervous system pathogens, gastrointestinal pathogens, fungalpathogens, HCV pathogens, gram positive bacteria, or gram negativebacteria from a patient sample.

In some example embodiments in accordance with the disclosed technology(example G1), a method for assessing electrical connection integrity ofan assay cartridge interfaced with an assay processing device includesestablishing an electrical connection between the assay cartridge andthe assay processing device; measuring electrical signals to determineimpedance values associated with at least two circuits between the assaycartridge and the assay processing device; organizing the impedancevalues to form a new data stream; analyzing the new data stream todetermine a quality factor; and sending a command signal for initiatingan assay procedure when the quality factor is at or above apredetermined standard.

Example G2 includes the method of example G1, further comprising sendinga command signal for ejecting the assay cartridge from the assayprocessing device when the quality factor is below the predeterminedstandard.

Example G3 includes the method of example G1, wherein organizing theimpedance values includes reordering the impedance values into alowest-to-highest monotonical sequence, or wherein organizing theimpedance values includes reordering the impedance values into ahighest-to-lowest monotonical sequence.

Example G4 includes the method of example G1, further comprising, priorto or after organizing the impedance values, excluding one or moreimpedance values.

Example G5 includes the method of example G1, wherein organizing theimpedance values comprises reordering the impedance values, which insome examples can be based on a predetermined reference order or aplurality of predetermined reference orders.

Example G6 includes the method of example G5, wherein the predeterminedreference order or plurality of predetermined reference orders isproduced from an analysis of internal and external data that define apattern of impedance values associated with the corresponding circuitsbetween the assay cartridge and the assay processing device.

Example G7 includes the method of example G1, wherein organizing theimpedance values comprises reordering the impedance values based on aprior reference order at least partially determined by an average ofprior valid runs on the assay processing device.

Example G8 includes the method of example G1, wherein the quality factoris based on one or more parameters selected from a group consisting of acorrelation coefficient (R²), a scaled error of fit for an electrode(EFT), a standard error of fit for a run (RFT), slope of the linecreated by the new data stream, intercept of the line created by the newdata stream and a tolerance difference value wherein the tolerancedifference value includes a difference of an R² associated with adifferent assay cartridge and the R² associated with the assaycartridge, or a difference of an RFT associated with a different assaycartridge and the RFT associated with the assay cartridge, or adifference of an EFT associated with a different assay cartridge and theEFT associated with the assay cartridge.

Example G9 includes the method of example G1, wherein the assaycartridge includes reagents to assay a panel of respiratory pathogens,central nervous system pathogens, gastrointestinal pathogens, fungalpathogens, HCV pathogens, gram positive bacterial pathogens, or gramnegative bacterial pathogens from a patient sample.

In some example embodiments in accordance with the disclosed technology(example G10), a method for assessing electrical connection integrity ofa first device and second device includes establishing an electricalconnection between the first device and second device; measuringelectrical signals to determine a first data block associated with atleast three electrodes on the first device; organizing the first datablock to form a second data block; analyzing the second data blockaccording to a first factor; and sending a signal for initiating aprocedure when the first factor is at or above a predetermined standard.

Example G11 includes the method of example G10, further comprisingsending a signal for disconnecting the first device from the seconddevice when the first parameter is below the predetermined standard.

Example G12 includes the method of example G10, wherein organizing theimpedance values includes reordering the impedance values monotonicallyor based on a predetermined reference order.

Example G13 includes the method of example G10, wherein organizing theimpedance values includes reordering the impedance values based on morethan one predetermined reference order.

Example G14 includes the method of example G10, wherein the electricalsignal is applied at a frequency between 10 kHz and 100 kHz.

Example G15 includes the method of example G10, further comprisinganalyzing the second data block according to a second factor and sendinga signal for initiating a procedure when the first factor and secondfactor satisfy a predetermined standard.

In some example embodiments in accordance with the disclosed technology(example G16), an assay processing device for assaying a patient sample,comprising an electronic unit that interfaces with a printed circuitboard (PCB) on an assay cartridge, an impedance module, a patternmodule, and a qualifier module.

Example G17 includes the assay processing device of example G16, whereinthe impedance module is configured to measure an electrical signal todetermine an impedance value associated with at least some circuitsbetween the assay cartridge and assay processing device; (ii) whereinthe pattern module organizes the impedance values to form a new datastream, (iii) wherein the qualifier module analyzes the new data streamto evaluate a quality factor and sends a command signal for initiatingan assay procedure when the quality factor is at or above apredetermined standard.

Example G18 includes the assay processing device of example G16, whereinthe qualifier module sends a command signal to a control module forejecting the assay cartridge from the assay processing device when thequality factor is below the predetermined standard.

Example G19 includes the assay processing device of example G16, whereinthe pattern module organizes the impedance values into alowest-to-highest monotonical sequence, or into a highest-to-lowestmonotonical sequence or on a predetermined reference order.

Example G20 includes the assay processing device of example G16, whereinthe pattern module and qualifier module are on a remote device.

Example G21 includes the assay processing device of example G16, whereinthe impedance module, the pattern module and the qualifier module are onthe electronics unit.

Example G22 includes the assay processing device of example G16, whereinthe impedance module includes a signal generator and an impedancemeasurement apparatus, wherein the signal generator generates and emitsa current pulse or a sequence of current pulses, and the impedancemeasurement apparatus measures an electrical signal to determine animpedance value associated with at least some circuits between the assaycartridge and assay processing device.

Example G23 includes the assay processing device of example G16, theassay processing device operable to implement the method of any ofexamples G1-G9.

In general terms, systems and methods of measuring impedance aredisclosed. In some specific embodiments, systems and methods formeasuring an electrical connection between a PCB and a device aredisclosed. Various example implementations of systems and methods aredescribed herein for measuring the contact impedance between two circuitboards.

In various examples, the disclosed systems and techniques are capable ofobtaining an electrical characteristic of a circuit assembly connectedto a working device, which includes measuring the impedance at eachelectrode, reordering the impedance values and determining if aconnection exists between the circuit assembly and working device as afunction of the re-order.

According to one aspect, provided is an article including a storagemedium having instructions that, when executed by a computing platform,result in execution of a method for data analysis, the method comprisingthe steps of a) receiving an input data block; b) comparing one or morecharacteristics of each input data block with one or more previouslyprocessed input data blocks; c) rearranging the input data block tomatch the order of the previously processed data blocks to form a newdata block; d) determining if the new data block is within predefinedparameters; e) processing the cartridge if the new data block is withinpredefined parameters or ejecting the cartridge if the new data block isnot within predefined parameters.

According to another aspect, provided is an apparatus for datacomparison, the apparatus comprising: a) an input module that receivesan input data stream; b) a comparator that compares each input datastream with each of a predetermined number of previously processed inputdata streams and wherein the comparator rearranges the input data streamto match the order of the previously processed input data stream tocreate a new data stream; and c) a qualifier that determines if the newinput data stream is within predefined parameters.

According to another aspect, provided is a system for data comparison,the system comprising: a) a cartridge interface; b) an input modulecoupled to the cartridge interface that receives an input data stream;c) a processor; d) a memory coupled to the processor; e) a comparatorthat compares the new data stream with at least one previously processeddata blocks and creates a new data stream; and f) a qualifier coupled tothe comparator that determines if the new input data stream matchespredefined parameters.

In some aspects, a system includes an assay cartridge including a PCBhaving a plurality of electrical interface connections; and an assayprocessing device including a cartridge bay having an electronic unitthat interfaces with the assay cartridge when the assay cartridge isinserted into the cartridge bay, wherein the electronic unit includes aplurality of electrical conductor sites to contact at least some of theplurality of electrical interface connections of the assay cartridgePCB, wherein the assay processing device is configured to conduct apreflight test in which impedance values for each electrode circuit arerearranged and assessed to determine the electrical connection integrityof the PCB of the assay cartridge with the electronic unit of thecartridge bay prior to implementing the assay.

Implementations of the subject matter and the functional operationsdescribed in this patent document can be implemented in various systems,digital electronic circuitry, or in computer software, firmware, orhardware, including the structures disclosed in this specification andtheir structural equivalents, or in combinations of one or more of them.Implementations of the subject matter described in this specificationcan be implemented as one or more computer program products, i.e., oneor more modules of computer program instructions encoded on a tangibleand non-transitory computer readable medium for execution by, or tocontrol the operation of, data processing apparatus. The computerreadable medium can be a machine-readable storage device, amachine-readable storage substrate, a memory device, a composition ofmatter effecting a machine-readable propagated signal, or a combinationof one or more of them. The term “data processing unit” or “dataprocessing apparatus” encompasses all apparatus, devices, and machinesfor processing data, including by way of example a programmableprocessor, a computer, or multiple processors or computers. Theapparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a stand-alone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Computer readable media suitable for storingcomputer program instructions and data include all forms of nonvolatilememory, media and memory devices, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

It is intended that the specification, together with the drawings, beconsidered exemplary only, where exemplary means an example. As usedherein, the singular forms “a”, “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. Additionally, the use of “or” is intended to include“and/or”, unless the context clearly indicates otherwise.

The term “about” means encompassing plus or minus 10%. For example,about 90% may refer to a range encompassing, for example, between 81%and 99%. As used herein, the term “about” is synonymous with the termapproximately.

The disclosed system and methods address device-centric challenges ofphysically testing electrical connections between circuit assembliesinterfaced to operate an electronic device, such as an assay device.Embodiments of the disclosed methods are necessarily rooted in computertechnology to specifically overcome problems arising when connecting twocircuit assemblies and improve the functioning of the electronic deviceby using computerized analytical processing techniques to diagnosemalfunctions or inefficiencies and/or dynamically alter an outputproduced by the electronic device.

While this patent document contains many specifics, these should not beconstrued as limitations on the scope of any invention or of what may beclaimed, but rather as descriptions of features that may be specific toparticular embodiments of particular inventions. Certain features thatare described in this patent document in the context of separateembodiments can also be implemented in combination in a singleembodiment. Conversely, various features that are described in thecontext of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in this patent document should not be understoodas requiring such separation in all embodiments.

Only a few implementations and examples are described, and otherimplementations, enhancements and variations can be made based on whatis described and illustrated in this patent document.

What is claimed is:
 1. A method for assessing electrical connectionintegrity of an assay cartridge interfaced with an assay processingdevice, comprising: establishing an electrical connection between theassay cartridge and the assay processing device; measuring electricalsignals to determine impedance values associated with at least twocircuits between the assay cartridge and the assay processing device;organizing the impedance values to form a new data stream; analyzing thenew data stream to determine a quality factor; and sending a commandsignal for initiating an assay procedure when the quality factor is ator above a predetermined standard, wherein the quality factor is basedon one or more parameters selected from a group consisting of acorrelation coefficient (R2), a scaled error of fit for an electrode(EFT), a standard error of fit for a run (RFT), slope of the linecreated by the new data stream, intercept of the line created by the newdata stream, and a tolerance difference value, wherein the tolerancedifference value comprises a difference of an R2 associated with adifferent assay cartridge and the R2 associated with the assaycartridge, or a difference of an RFT associated with a different assaycartridge and the RFT associated with the assay cartridge, or adifference of an EFT associated with a different assay cartridge and theEFT associated with the assay cartridge.
 2. The method of claim 1,further comprising: sending a command signal for ejecting the assaycartridge from the assay processing device when the quality factor isbelow the predetermined standard.
 3. The method of claim 1, whereinorganizing the impedance values comprises reordering the impedancevalues into a lowest-to-highest monotonical sequence, or whereinorganizing the impedance values comprises reordering the impedancevalues into a highest-to-lowest monotonical sequence.
 4. The method ofclaim 1, further comprising, prior to or after organizing the impedancevalues, excluding one or more impedance values.
 5. The method of claim1, wherein organizing the impedance values comprises reordering theimpedance values based on a predetermined reference order or a pluralityof predetermined reference orders.
 6. The method of claim 5, wherein thepredetermined reference order or plurality of predetermined referenceorders is produced from an analysis of internal and external data thatdefine a pattern of impedance values.
 7. The method of claim 1, whereinorganizing the impedance values comprises reordering the impedancevalues based on a prior reference order at least partially determined byan average of prior valid runs on the assay processing device.
 8. Themethod of claim 1, wherein the assay cartridge comprises reagents toassay a panel of respiratory pathogens, central nervous systempathogens, gastrointestinal pathogens, fungal pathogens, HCV pathogens,gram positive bacterial pathogens, or gram negative bacterial pathogensfrom a patient sample.
 9. A method for assessing electrical connectionintegrity of a first device and second device comprising: establishingan electrical connection between the first device and second device;measuring electrical signals to determine a first data block associatedwith at least three electrodes on the first device; organizing the firstdata block to form a second data block; analyzing the second data blockaccording to a first factor; and sending a signal for initiating aprocedure when the first factor is at or above a predetermined standard,wherein the first factor is based on one or more parameters selectedfrom a group consisting of a correlation coefficient (R2), a scalederror of fit for an electrode (EFT), a standard error of fit for a run(RFT), slope of the line created by the second data block, intercept ofthe line created by the second data block, and a tolerance differencevalue, wherein the tolerance difference value comprises a difference ofan R2 associated with a different device and the R2 associated with thefirst or second device, or a difference of an RFT associated with adifferent device and the RFT associated with the first or second device,or a difference of an EFT associated with a different device and the EFTassociated with the first or second device.
 10. The method of claim 9,further comprising: sending a signal for disconnecting the first devicefrom the second device when the first parameter is below thepredetermined standard.
 11. The method of claim 9, wherein organizingthe impedance values comprises reordering the impedance valuesmonotonically or based on a predetermined reference order.
 12. Themethod of claim 9, wherein organizing the impedance values comprisesreordering the impedance values based on more than one predeterminedreference order.
 13. The method of claim 9, wherein the electricalsignal is applied at a frequency between 10 kHz and 100 kHz.
 14. Themethod of claim 9, further comprising: analyzing the second data blockaccording to a second factor and sending a signal for initiating aprocedure when the first factor and second factor satisfy apredetermined standard.
 15. An assay processing device for assaying apatient sample, comprising: an electronic unit that interfaces with aprinted circuit board (PCB) on an assay cartridge, an impedance module,a pattern module, and a qualifier module, wherein the impedance moduleis configured to measure an electrical signal to determine an impedancevalue associated with at least some circuits between the assay cartridgeand assay processing device; (ii) wherein the pattern module organizesthe impedance values to form a new data stream, (iii) wherein thequalifier module analyzes the new data stream to evaluate a qualityfactor and sends a command signal for initiating an assay procedure whenthe quality factor is at or above a predetermined standard, wherein thequality factor is based on one or more parameters selected from a groupconsisting of a correlation coefficient (R2), a scaled error of fit foran electrode (EFT), a standard error of fit for a run (RFT), slope ofthe line created by the new data stream, intercept of the line createdby the new data stream, and a tolerance difference value, wherein thetolerance difference value comprises a difference of an R2 associatedwith a different assay cartridge and the R2 associated with the assaycartridge, or a difference of an RFT associated with a different assaycartridge and the RFT associated with the assay cartridge, or adifference of an EFT associated with a different assay cartridge and theEFT associated with the assay cartridge.
 16. The assay processing deviceof claim 15, wherein the qualifier module sends a command signal to acontrol module for ejecting the assay cartridge from the assayprocessing device when the quality factor is below the predeterminedstandard.
 17. The assay processing device of claim 15, wherein thepattern module organizes the impedance values into a lowest-to-highestmonotonical sequence, or into a highest-to-lowest monotonical sequenceor on a predetermined reference order.
 18. The assay processing deviceof claim 15, wherein the pattern module and qualifier module are on aremote device.